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How the United States Mainstream Media frames Foreign Policy Issues: A Comparative Case Study on the Battle of Aleppo and the Battle of Mosul

by Emma Bihan-Poudec , Central European University

In 2002, New York Times reporter Judith Miller published an article affirming that Saddam Hussein was in possession of arms of mass destruction, relying on an anonymous official source (2002). The allegations were later disproved, and this article became the source of heated debates surrounding ethics of media-state relations. In 2004, the outlet admitted the information they received, “was insufficiently qualified or allowed to stand unchallenged” (The Intercept, 2015). This example of collusion highlights the concerns of ethics in reporting and it is fair to wonder whether this alarming admission influences the culture of reporting. McCombs Maxwell describes the press as, “the citizenry’s principal source of information” (2005), especially on foreign policy issues, out of people’s perceptions. The complicity of US media in foreign interventions has been denounced by scholars such as Chomsky (1994) and Entman (2004), who established the correlation between certain media coverage and elite interests.                              

 As foreign interventions have consequences on international security, the media has a responsibility to portray conflicts accurately. With the evolution of the media landscape and the emergence of the internet as a primary source of information, some argue that media landscapes are more pluralist and independent (Bennett, 2006). Thus, this research aims to establish whether such biases were observed in the coverage of The Battle of Aleppo and the Battle of Mosul, through qualitative content analyses. This paper answers the following research question: Does mainstream media display a bias in its coverage depending on the foreign policy of the US government? This paper will conclude that the analyzed mainstream media outlet displayed a bias while covering these two foreign policy issues and that this bias was in accordance with the official position of the US government. To do so, the relevant literature on media-state relations and framing is analyzed; the methodology is then outlined; altogether to finally proceed with the qualitative content analysis. Finally, I will conclude that this study validates the hypothesis and provides evidence towards a systematic bias of the U.S. Media.

Literature Review

Academics widely recognize the interdependence between policies and media. This interdependence directed scholars to specifically focus on techniques used by journalists to analyze whether the mainstream media illustrated any such bias in its coverage and effectively fulfilling its function of an independent watchdog. These systemic and established journalistic techniques provide a comparative advantage while studying media bias. On one hand, the Cable News Network (CNN) effect school views media as a powerful independent regulating tool enough to force governments to change their agenda (Robinson, 2002). Scholars such as Livingstone (2000) considers the media as a neutral tool, conveying the elite’s views, without any power in foreign policy decisions. On the contrary, Chomsky (1994) attributes the great powers of news outlets to elites. Chomsky considers that the mass media inculcates, “individuals with the beliefs that will integrate them into the institutional structures of the larger society” (1994). The Manufacturing Consent theory argues the media is a biased actor working in favor of corporate interests. More studies highlight the omnipresence of official sources in news coverage, which has been widely accepted in the literature (Bennett, 2006). To inculcate beliefs to the readers, journalists use techniques such as framing, which, “promotes a ‘perceived reality’, endorses a specific problem definition, moral evaluation, and a treatment recommendation” (Entman, 1993, 51). For the purpose of this study, framing is defined as “a central organizing theme that can consist of the use of texts.” (Dimitrova and Stromback, 2005)

Framing, within this paper, applies to foreign policy, which defines a government’s interaction with other states, regarding specific issues such as the cases used in this study. Some particular studies address productive framing, which implies an intention to portray an event in a positive or negative light (Mintz, 2003). This research aligns itself along scholars such as Entman, who used framing to highlight bias between cases in media coverage, while it fits more broadly into the theory of Manufacturing Consent, by Chomsky and Hermann (1994), which establishes a theoretical framework for the systematic bias of mainstream media overall.  The framing analysis of the Mosul and Aleppo cases will provide evidence in support of or contradict systematic media bias while contributing to the literature both empirically and analytically.

Methodology

This study substantially builds upon the previous work of Chomsky and Entman (2004), who established a pattern of systematic bias from mainstream US media. A deductive approach is adopted, through qualitative methods, for two case studies: the Battle of Aleppo and the Battle of Mosul. The following hypothesis will be deductively tested:

The media coverage from these outlets is consistently different across cases and reflects the official position of the US government, as supported by the differential use of the six studied frames.

Thus, this paper tests whether the official position of the US government explains the variance in the framing used in the media coverage of these two cases. The observation of this variance is based on comparative analyses of frames used in the previous study of Dimitrova and Stromback (2005). A detailed Coverage Codebook of the author’s methodology allowed for specific examples of frames and criteria. This case study observes the most similar systems design (Pfetsch and Esser, 2004) as both presented military operations similar tactics, targets, settings, and objectives. Both resulted in liberations. I will use three outlets from the United States that represent the diversity of the mediatic landscape: The New York Times, ABC News, and Fox News. The New York Times is considered a liberal outlet that is often referred to as an agenda-setter (Dimitrova and Stromback, 2005). Fox News reaches a more conservative audience, mainly those who are aligned with the Republican party ideology, whereas ABC is more centrist. The online database LexisNexis was used to select articles from the New York Times and ABC News, whereas the website of Fox News was used to select articles from this media outlet. The timeframe of the Battle of Aleppo went from August 2016 to February 2017; February 2017 to August 2017 for the Battle of Mosul. The keywords ‘Aleppo’ and ‘Mosul’ were specifically used to refine the search to yield the relevant articles:

                                                   Mosul                         Aleppo

              NYTimes                           96                              175                            

             ABC News                         17                                21

              Fox News                         188                             278

              Total                                  301                             474                 

Figure 1: Relevant articles selected for this study

A total of 775 articles were selected for the content analysis, which establishes whether the headlines presented a positive or negative tone. Words used over 50 times in headlines were determined through an analysis with the Nvivo12 software and appears in Figure 1 and Figure 2. Furthermore, the study was completed by a qualitative discourse analysis, for which one article per outlet per case was selected. The following articles were selected:

NYT, Mosul: Iraqi Prime Minister Arrives in Mosul to Declare Victory Over ISIS, 9th July 2019.

NYT, Aleppo: Assad’s lesson from Aleppo: Force works, with few consequences, 16th December 2016.

Fox News, Mosul: 5 things to know about Iraq’s Mosul, 27th September 2017.

Fox News, Aleppo: 5 things to know about Syria’s Aleppo, 22nd December 2016.

ABC News, Mosul: Iraqis close to victory against ISIS; U.S-backed troops fighting for Mosul. 9th July 2017.

ABC News, Aleppo: The children of Aleppo, families flee city, Assad claims victory, 15th December 2016.

The selection permitted to establish the overarching opinion of the respective media outlet. The analyses were based on the following frames: (1) the military conflict frame, which emphasizes military actors and actions; (2) the human-interest frame, which highlights the human impact of conflict; (3) the responsibility frame, which indicates the responsible actor; (4) the violence of war frame which concentrates on destruction; (5) the diagnostic frame, which establishes the reasons; (6) finally, the prognostic frame, which discusses implications. Finally, the type of source and the moral terminology were controlled for.

Data Analysis

 In total, 775 headlines were analysed, separately, according to the case. The first emerging finding is the difference in volume between articles (refer to Figure 1). All outlets, except for ABC News, covered Aleppo more extensively. In the case of Aleppo, the articles are longer and diverge towards international issues. Contrastingly, the articles on Mosul are shorter and focus on military operations. There are significantly more articles available on Aleppo from the New York Times and Fox News, illustrating the framing technique of ‘contrasting magnitude’, which, “magnifies those elements of depicted reality that favor one side’s position” (Entman, 2004, p30). While these two battles caused thousands of civilian casualties, in densely populated areas, the media magnified the Battle of Aleppo, aligning its coverage with US government foreign policy (US Department of State, 2020). The Nvivo12 ‘cloud word’ tool permitted to identify the words used in the headlines with a minimum frequency of 50:

Figure2: Mosul coverage cloud word

Figure 3: Aleppo coverage cloud word

The use of different vocabularies between the two cases is apparent. In the case of Mosul, adjectives such as ‘liberation’ and ‘victory’ appear systematically, attaching a positive moral terminology, which again aligns with the position of the US government (US Department of Defence, 2017). The keywords focus principally on the military operations and advances of the coalition against the Islamic State (ISIS). The words ‘deaths’ and ‘killed’ were mainly linked to the Islamic State, denouncing the actions of the adversary. Contrastingly, to cover Aleppo, adjectives such as ‘victory’ or ‘liberation’ are not used. The headlines are more focused on the death toll and devastation caused by military operations, expressing strong moral condemnations. Words such as ‘siege’ are prominent to describe Aleppo, emphasizing the violence of the war frame.

However, the software analysis of the headlines solely cannot capture the subtilty of framing. As the software analyses single words, the combination of words or rhetorical devices are excluded, which emphasizes the need for a complementary manual analysis. A particular headline from the New York Times summarises this established narrative, “U.S. forces play a crucial role against ISIS in Mosul” (New York Times, 2017). Other recurrent words are “retake”, “advance”, “progress”, which can be aimed to incite a positive judgment from readers. Keywords used over thirty times to describe the Battle of Aleppo were “agony”, “failed”, and “hell”. An August 3rd, 2016 article from the New York Times had for headline, “The case for (finally) bombing Assad.” No headlines on Aleppo focused on actions by rebel groups, some of which had the US government supports. The analysis of headlines highlights a significant contrast, reflecting the position of the US government in both conflicts and providing additional evidence towards bias.

              Therefore, an analysis of six selected articles permits to deepen the analysis of the framing used in both cases and strengthen the patterns observed. The findings establish a consistent difference in the coverage of these two cases. On the one hand, the moral terminology on the Battle of Aleppo is negative. While describing the battle, the coverage emphasizes the disastrous consequences, the civilian casualties, and the injustices of war. The use of pejorative adjectives is consistent and primarily used besides mentioning the Syrian government of President Bashar Al Assad. On the other hand, the articles covering the Battle of Mosul use a positive tone, painting a noble account of a battle fiercely won through the use of glorifying adjectives. Overall, no outlet in this research covered either battle neutrally. Fox News, in particular, is the outlet that focuses on the military frame the most, rarely employing the human-interest frame. Moreover, the negative tone of the New York Times, on the issue of Aleppo, provides an interesting finding. The newspaper principally used these three frames: the violence of war, responsibility, and military conflict. The outlet addresses the liberal platform of the United States, traditionally less inclined to support military interventions. However, it observes an aggressive and conservative approach in the case of Aleppo, which particularly echoes the New York Times advocating for an invasion of Iraq in 2002. Therefore, it is fair to conclude that the New York Times demonstrates a bias in this case. Similarly, ABC News did not offer a different perspective on these two conflicts. It used the military frame less and used the human-interest frame more as opposed to the other outlets. It focused on the civilians’ plight in both conflicts but adopted a negative tone on Aleppo, in contrast with the positive tone used to cover Mosul. As Mutz explained, one-sided coverage leads to a ‘consensus heuristic’, which means that interpretations of certain events function as clues to which viewpoints are valid or acceptable (1998). These clues, in the cases of Mosul and Aleppo, are given through the volume of media content, the framing utilized, and the use of systematic negative or positive adjectives.

              The main finding that emerges from the use of sources across these two cases is the use of official versus unofficial sources. A discrepancy in the use of official sources in Mosul and unofficial sources in Aleppo is noticeable. According to Bennett’s ‘indexing hypothesis’, non-official sources solely appear in news stories when their opinion are in official circles (1990). Indeed, the media uses the ‘rebels’ as sources in the headlines published on Aleppo, reflecting the US government policy of supporting rebel groups such as the Free Syrian Army in Aleppo (Foreign Affairs, 2019). A striking finding is the regular mention of Aleppo’s battle as the ‘fall’, while Mosul is referred to as a ‘liberation’. A significant correlation between the frames and the sources can be observed. The use of military sources correlated with repetitive use of the military conflict frame and was less likely to be used alongside the human interest and prognostic frames. Individuals' stories of civilians or soldiers were quoted principally alongside the human-interest frame and with a very low frequency alongside the military conflict frame, which emphasized facts over personal accounts.

The New York Times consistently used official sources and did not quote any opponent of the United States actions in both cases. The Syrian government was not quoted once across all outlets, reflecting the wide opposition of the Western world towards the Assad regime. ABC News quoted official sources in the case of Mosul and civilians in the case of Aleppo. Fox News focused mainly on military and governmental sources to report on the victory in Aleppo and only cited a human rights observatory while covering Aleppo. The findings outlined in this section are consistent with the worldwide trend that media mainly relays the voice of their government while covering international events (Mermin, 1999). This analysis thus validates the hypothesis of the media coverage being consistently different and echoing the official position of the US government, as supported by the differential use of the six studied frames, the use of sources, and the moral terminology attached to the analyzed framing.

Through a qualitative content analysis, this research validated the following hypothesis: the media coverage from these outlets is consistently different across cases and reflects the official position of the US government, as supported by the differential use of the six studied frames. This paper provides empirical evidence towards a bias in the media, through the use of frames, tone of the coverage, and sources used. The findings apply across all outlets studied, with the content consistent with the official position of the US government. The results show that the mainstream media focused on some aspects of the reality of war such as military success and victory, however, it excluded some other aspects such as human suffering. Nevertheless, the limitations of this study in terms of resources and sample size are worth mentioning. More resources should be devoted towards larger samples which would strengthen these results. These limitations do not, however, revoke the importance of this study.

Note: The Codebook used for this study is available upon request from Dr. Dimitrova and Dr. Stromback.

Bennett, W, Lawrence R, Livingston S. 2006. None dare call it torture: indexing and the limits of press independence in the Abu Ghraib scandal. J. Commun. 56. pp:467–85. 

Bennett, W. 1990. Toward a theory of press-state relations in the United States. Journal of Communication. 40(2). pp:103–125. 

Chomsky, N. and Herman, N. 1994. Manufacturing Consent: The political economy of the mass media. 1st ed. London: Vintage. pp:298-302. 

Dimitrova, D. and Stromback, J. 2005. Mission accomplished? Framing of the Iraq war in the elite newspapers in Sweden and the United Stated. International Communication Gazette.  67(5). pp:399–417. 

Entman, R. 2004. Projections of Power. Chicago, IL: University of Chicago Press. 

Entman, R. 1993. Framing: Towards clarification of a fractured paradigm. Journal of Communication. 43(4). pp: 51–58. 

Foreign Affairs. 2019. The End of the CIA Program in Syria. Foreign Affairs. https://www.foreignaffairs.com/articles/syria/2017-08-02/end-cia-program... .

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Fox News. 2016. 5 things to know about Syria’s Aleppo. Fox News. https://www.foxnews.com/world/5-things-to-know-about-syrias-aleppo .

Livingston, S. 2000. Transparency and the news media. In B. Finel & K. Lord (ed), Power and conflict in the age of transparency. pp: 257–285. New York: St. Martins Press. 

McCombs, M. 2005. The agenda-setting function of the press. In: Overholser G and Jamieson KH (ed). Institutions of American Democracy: The Press. New York: Oxford University Press. pp: 156-168. 

Mermin, J. 1999. Debating war and peace: Media coverage of U.S. intervention in the post- Vietnam era. Princeton, NJ: Princeton University Press. 

Mintz, A., Redd, S. 2003. Framing Effects in International Relations. Synthese. 135(2). pp:193-213. https://www.jstor.org/stable/20117363 .

Mutz, Diana C. 1998. Impersonal Influence: How Perceptions of Mass Collectives Affect Political Attitudes. New York: Cambridge University Press.

New York Times. 2002. Threats and responses: The Iraqis; U.S says Hussein intensifies quest for a bomb part. New York Times. https://www.nytimes.com/2002/09/08/world/threats-responses-iraqis-us-say... .

The Intercept, 2015. From the Editors; The Times and Iraq. The Spirit of Judy Miller Is Alive and Well at the NYT, and It Does Great Damage. https://theintercept.com/2015/07/21/spirit-judy-miller-alive-well-nyt-gr... .

New York Times. 2017. U.S. Forces Play Crucial Role Against ISIS in Mosul. New York Times. https://www.nytimes.com/2017/02/26/world/middleeast/mosul-iraq-american-... .

New York Times. 2017. Assad’s Lesson from Aleppo: Force Works, With Few Consequences. New York Times. https://www.nytimes.com/2016/12/16/world/middleeast/syria-aleppo-assad-a... .

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Robinson, P. 2002. The CNN effect: The myth of news, foreign policy and intervention. New York: Routledge. Chap1. 

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United States Department of Defense. 2017. Iraqis Fight for Western Mosul in Tough Battle Against ISIS. March 13, 2017. https://www.defense.gov/Explore/News/Article/Article/1111557/iraqis-figh... …/.

Partisanship, Propaganda, and Disinformation: Online Media and the 2016 U.S. Presidential Election

Nikki Bourassa

Ethan Zuckerman

Yochai Benkler

Robert Faris

Hal Roberts

Bruce Etling

Executive Summary

In this study, we analyze both mainstream and social media coverage of the 2016 United States presidential election. We document that the majority of mainstream media coverage was negative for both candidates, but largely followed Donald Trump’s agenda: when reporting on Hillary Clinton, coverage primarily focused on the various scandals related to the Clinton Foundation and emails. When focused on Trump, major substantive issues, primarily immigration, were prominent. Indeed, immigration emerged as a central issue in the campaign and served as a defining issue for the Trump campaign.

We find that the structure and composition of media on the right and left are quite different. The leading media on the right and left are rooted in different traditions and journalistic practices. On the conservative side, more attention was paid to pro-Trump, highly partisan media outlets. On the liberal side, by contrast, the center of gravity was made up largely of long-standing media organizations steeped in the traditions and practices of objective journalism.

Our data supports lines of research on polarization in American politics that focus on the asymmetric patterns between the left and the right, rather than studies that see polarization as a general historical phenomenon, driven by technology or other mechanisms that apply across the partisan divide.

The analysis includes the evaluation and mapping of the media landscape from several perspectives and is based on large-scale data collection of media stories published on the web and shared on Twitter.

Overview of Methods

Cross-linking patterns between media sources offer a view of authority and prominence within the media world.

The sharing of media sources by users on Twitter and Facebook provides a broader perspective on the role and influence of media sources among people engaged in politics through Twitter and Facebook.

The differential media sharing patterns of Trump and Clinton supporters on Twitter enable a detailed analysis of the role of partisanship in the formation and function of media structures.

Content analysis using automated tools supports the tracking of topics over time among media sources.

Qualitative media analysis of individual case studies enhances our understanding of media function and structure. 

Key Takeaways

Donald Trump succeeded in shaping the election agenda. Coverage of Trump overwhelmingly outperformed coverage of Clinton. Clinton’s coverage was focused on scandals, while Trump’s coverage focused on his core issues.

Read the Introduction

Related press coverage: Down the Breitbart Hole  ( New York Times ) Study: Breitbart-led right-wing media ecosystem altered broader media agenda  ( Columbia Journalism Review ) Researchers Examine Breitbart's Influence On Election Information  (NPR) The great divide: The media war over Trump  (CBS)

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Top 3 Social Media Case Studies to Inspire You in 2024

Discover three successful social media case studies from top brands and learn how to create one. Benefit from their strategies and mistakes to ensure the success of your next campaign.

Social media is every marketer’s safe haven for branding and marketing.

And why not?

More than 50% of the population is active on social media, and more are signing up with every passing second.

In a recent poll by HubSpot, 79% of the respondents have made a purchase after seeing a paid advertisement on social media .

This isn’t just a happenstance.

It’s the constant efforts that these brands put behind their dynamic presence on social media, that counts.

But how do they captivate their customers’ attention for this long despite the budding competitors?

Well, that’s something that we’ll reveal in this blog.

We shall assess 3 different social media case studies by top brands who are best in their niches. Their game is simple yet effective.

How effective? Let’s take a look.

Social Media Case Study 1: Starbucks

Starbucks and social media are a match made in heaven. Being one of the sensational brands online, they are stirring the social media world with their strong presence.

They brew the right content to elevate the experiences of their coffee lovers. But how do they nail marketing with perfection every single time? Let’s find out.

Starbucks in Numbers

Starbucks mastered the advertising transition from offline fame to online undertaking. They use each social media with a varied goal to target pitch-perfect reach. Drawing in more customers than ever before, they strike the right balance in content across multiple platforms.

Key Takeaways

Though not every company has a Starbucks budget to promote and spend lavishly on social media marketing, here are some quick takeaways that will undoubtedly help.

1. Chasing Trends

Be it any event, brands must take the advantage to showcase their viewpoints and opinions. Successful brands like Starbucks jump into the bandwagon and leave no stone unturned to make their voice count in the trending list.

Here’s one such social media campaign example from Starbucks.

Starbucks is a firm believer in LGBTQ+ rights. When the pride wave surged, Starbucks came forward and reinstated its belief through the #ExtraShotOfPride campaign.

Starbucks joined hands with the Born This Way Foundation to raise $250K to support the LGBTQ+ community. Throughout the social media campaign, they shared quotes and stories of various Starbucks employees cherishing the pride spirit.

2. Less is More

Social media is not about quantity but quality. Starbucks follows the “less is more” principle to maintain the quality standards, even in the caption. Spamming followers’ feeds with constant posting is a big no-no. Starbucks shares 5-6 posts per week on Instagram and 3-4 weekly posts on Facebook .

Creative and crisp! That’s what defines a Starbucks caption. This post with 111+k likes is no exception. Nothing is better than a minimalist post with a strong caption.

3. User Generated Content is the King

Ditch the worry of creating content every day when you can make use of user generated content. Starbucks makes sure to retweet or post its loyal customers’ content. User generated content postings starkly improve brand credibility.

Look at this Facebook post made out of customers’ tweets. The new Oatmilk drink got the appreciation shower by some, and Starbucks couldn’t resist but share it with others. It saved them efforts on content brainstorming, plus they got free PR.

4. Building Rapport

Building rapport with the audience is an unsaid rule to brand fame. Social media has now taken the onus of dispensing quality service by aiding brands in prompting faster replies .

Starbucks is always on its toe to respond to customers actively solving concerns, expressing gratitude, or reposting. That kind of proactive service definitely deserves love and adoration.

5. Loads of campaigns

Starbucks is known for its innovative social media campaigns. Be it a new product launch or any festivity around the corner, Starbucks always turns up with a rewarding campaign.

In this social media campaign example, Starbucks introduced #RedCupContest with prizes worth $4500 during Christmas of 2016. A new entry came every 14 seconds.

The grand total of entries was a whopping 40,000 in just two days. Indeed Starbucks knows how to get the most out of the festive fever.

6. Content mix

Last but not least, the content mix of Starbucks is inspiring. They create tailored content for every platform.

The official youtube channel of Starbucks comprises content in varied hues. From recipes to even series, Starbucks is the ultimate pioneer of experimenting.

Even on Instagram, they use all the features like Guides, Reels, and IGTV without affecting their eye-popping feed. Starbucks also follows the design consistency for its aesthetic content mix.

Starbucks has proved time and again to be a customer-centric brand with their unrelenting efforts.

Social Media Case Study 2: Ogilvy & Mather

Ogilvy & Mather needs no introduction. Founded by David Ogilvy, the ‘Father of Advertising’ in 1948, the agency continues the legacy of revolutionizing marketing long before the advent of social media.

The iconic agency helps several Fortune 500 companies and more make a massive impact on their audiences worldwide.

Ogilvy & Mather knows its game too well and never fails to astonish. Not just high-profile clients, Ogilvy nails its marketing with perfection every single time.

Keep on reading.

Ogilvy & Mather in Numbers

They use social media to target pitch-perfect reach. Drawing in more hype than ever before, they know how to strike the right balance and bring out emotions with their heart-warming campaigns.

Not every company has David Ogilvy’s legacy or even affluent clients to boast of, but here are some quick takeaways that will undoubtedly help you become a pro marketer.

1. Integrating Values

Ogilvy stands apart from the crowd, creating trends. They leave no stone unturned to communicate values.

Proud Whopper is one such social media campaign by Ogilvy that was an instant hit on the internet. People were offered whoppers in rainbow-colored wrappers, with a note that said, “Everyone’s the same on the inside.” This was to reinstate the importance of LGTQ+ rights.

The campaign got 1.1 billion impressions, $21 million of earned media, 450,000 blog mentions, 7 million views, and became the #1 trending topic on Facebook and Twitter.

Ogilvy made a remarkable #Tbt video to honor this momentous event showcasing their supremacy in creating impactful campaigns.

2. Quality over Quantity

Ogilvy believes in the “ Quality supremacy ” to maintain their high standards, even in post captions.

Arbitrary posting isn’t a part of their agenda. They share 5-7 posts on Instagram and Facebook weekly.

Direct and very precise. That’s what defines an Ogilvy caption. This post is no exception. They have exhibited the success of their client work by describing the motive behind the campaign and sharing the ad they created for raising awareness.

3. Adding Credibility

Won awards? It’s time to boast! Because that’s the most authentic way of establishing trust among your clients. It bears proof of your excellence.

Look at this pinned Twitter post. Ogilvy won the Global Network of the Year by the very prestigious London International Awards. It also earned Regional Network of the year for Europe, the Middle East, Asia, and Europe.

What better than this to give its audience an idea about Ogilvy’s roaring success and undoubted potential?

4. Being Innovative

Building rapport with the audience is an unsaid rule to brand fame. And that’s why you need to tell stories. Social media has become an indispensable medium to spread your stories far and wide.

Ogilvy shares its historical tale of existence and how it has adapted to the challenges of the changing world. The team extensively talks about their adaptation to the latest trends to stay on top always.

5. Brainstorming Uniqueness

Being unique is what propels you on social media. People are always looking for brands that do something different from the herd. So your task each day is undeniably brainstorming unique content.

KFC wanted more of its customers to use its app. Well, Ogilvy and KFC decided to hide a secret menu in the app, which was a mass invitation for the download without being salesy at all. Results? Downloads up by 111% at launch!

6. Inspire Your Peeps

Inspiration is everywhere. But how do you channelize and mold it as per your brand guidelines? The renowned brands move their audience, filling them with a sense of realization. Who doesn’t seek validation? We all need quotes and inspiration to live by.

Ogilvy has dedicated its entire Pinterest profile to inspiration. The profile has numerous insightful infographics that encourage you to pursue marketing when your spirits run low. And that’s how it brings out the very essence of being the marketing leader: by inspiring its followers.

Got some good ideas for your branding? We have created templates and tools to help you execute them hassle-free. Tread on further and download the Trending Hashtag Kit for 2024 to get into action.

Social Media Case Study 3: PewDiePie

YouTube king with 111 Million subscribers on PewDiePie Channel, Felix Arvid Ulf Kjellberg, has defied all norms. One of the most prolific content creators of the decade, Felix was on the list of World’s 100 Most Influential People by Time Magazine in 2016.

Needless to say, he is still relevant to this day and has a massive following on social media. Not just for branding, the Swedish YouTuber leveraged social media to give himself a new identity and opened doors to fame and a successful career.

What was the cause of this extraordinary trajectory?

Let’s find out.

PewDiePie in Numbers

PewDiePie likes to keep his social media raw and unfiltered. That’s why subscribers love to have a glimpse of his everyday life and follow him on other social media platforms as well. Here’s a quick snapshot of that.

Felix took the early bird advantage and started creating content when it wasn’t even popular practice. We can’t go back in time, but we can definitely learn a lot from his social media success.

1. Start Now

If you are still skeptical about making the first move, then don’t. Stop waiting and experiment. It’s better late than never.

Social media is in favor of those who start early because then you create surplus content to hold your audience . You quench their thirst for more quality content.

PewDiePie started creating videos in 2011 and live-streamed his gaming sessions with commentaries. It was something new and completely original. Ever since, he has continued to make thousands of videos that entertain his audience.

2. Gather Your Tribe

Being a content creator, PewDiePie knows his act of engaging his audience very well. He strives to build lasting connections and encourages two-way communication. As a result, his followers like to jump onto his exciting challenges.

Felix treasures his gaming community. He frequently asks his followers to take screenshots and turn them into funny memes . He gives them tasks to keep them engaged and amused .

3. Collaboration and Fundraising

Once you reach the stage and gain popularity, people want to see more of you with their favorite personalities. That’s what Felix does.

He collaborates with multiple YouTubers and brands and puts out exclusive content for his followers. He also goes for multiple fundraising campaigns to support vital causes and social wellbeing.

Here’s one such social media campaign example. PewDiePie supported the CRY foundation and raised $239000 in just one day to bring a positive impact for children in India. He thanked all for their contribution and taking active participation towards a noble cause.

4. Keep it Real

Felix likes to keep his content fluff-free. You get to witness raw emotions from an unfiltered life. This instantly appeals to the audience and makes the posts more relatable .

Apart from that, he also uses storytelling techniques to narrate his experiences, adding a very personalized touch to each of the videos.

Here’s a video of Felix where he and Ken from CinnamonToastKen discuss what can be possibly done with a million dollars around the world. The topic is quite intriguing.

More than 3.8M people have watched it and 216K of them liked it as well, proving that you need not always sweat to create complex content. Even the simplest ones can make the cut.

How to Write a Social Media Marketing Case Study

Many small businesses struggle when it comes to social media marketing. But guess what? Small businesses can slay the competition with a powerful tool: the social media case study.

These social media case studies are success stories that prove your hustle is paying off. Here’s how to weave a case study that showcases your small business wins:

Building Your Brag Book

• Pick Your Perfect Project:  Did a specific social media campaign drive a surge in sales? Highlight a product launch that went viral. Choose a project with impressive results you can showcase.
• DIY Interview:  Don’t have a fancy marketing team? No worries! Record yourself talking about your challenges, goals, and the strategies that made a difference.
• Data Dive:  Track down social media analytics! Look for growth in followers, website traffic driven by social media, or engagement metrics that show your efforts are working.

Now that you have all the ingredients, it’s time to cook a brilliant case study

Crafting Your Case Study

• Headline Hunt:  Grab attention with a clear and concise headline. Mention your business name and a key achievement (e.g., “From 100 to 10,000 Followers: How We Grew Our Bakery’s Social Buzz”).
• Subheading Scoop:  Briefly summarize your success story in a subheading, piquing the reader’s interest and highlighting key takeaways.
• The Business Struggle:  Be honest about the challenges you faced before tackling social media. This will build trust and allow other small businesses to connect.
• DIY Social Strategies:  Share the social media tactics you used, such as engaging content formats, community-building strategies, or influencer collaborations.
• Numbers Don’t Lie:  Integrate data and visuals to support your story. Include charts showcasing follower growth or screenshots of top-performing posts.
• Simple & Straightforward:  Use clear, concise language that’s easy to understand. Bullet points and short paragraphs make your case study digestible and showcase your professionalism.

Remember: Your social media case study is a chance to celebrate your achievements and build businesses. So, tell your story with pride, showcase your data-driven results, and watch your brand recognition soar

Social media campaigns are winning hearts on every platform. However, their success rates largely depend on your year-round presence. That’s why being consistent really does the trick.

We’re sure you must have learned a few things from the above-mentioned social media case studies .

To excel further at your social media marketing, use our FREE Trending Hashtag Kit and fill your calendar with everyday content ideas.

On downloading, you get 3000+ hashtags based on each day’s theme or occasion. You also get editable design templates for hassle-free social media posting.

What are you waiting for? Download now.

Frequently Asked Questions

🌟 How do I start a social media campaign idea?

Here’s how you can start a social media campaign:

• Finalize your campaign goals
• Brainstorm personas
• Pick a social media channel
• Research your competitors and audience
• Finalize an idea that’s in trend
• Promote the campaign
• Start the campaign
• Track the performance

🌟 What are the different types of social media campaigns?

Different types of social media campaigns are:

• Influencer Campaigns
• Hashtag Challenges

🌟 Why is social media campaign important?

Social media campaigns have various benefits:

• Boost traffic
• Better Conversions
• Cost-effective Marketing
• Lead Generation
• PR & Branding
• Loyal Followers

🌟 What are some of the best social media campaign tools?

Some of the best social media campaign tools are:

• SocialPilot

🌟 What are the top social media sites?

The top social media sites are:

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the media equation

Inside the ‘Misinformation’ Wars

Journalists and academics are developing a new language for truth. The results are not always clearer.

By Ben Smith

On Friday afternoons this fall, top American news executives have dialed into a series of off-the-record Zoom meetings led by Harvard academics whose goal is to “help newsroom leaders fight misinformation and media manipulation.”

Those are hot topics in the news industry right now, and so the program at Harvard University’s Shorenstein Center on Media, Politics and Public Policy drew an impressive roster of executives at CNN, NBC News, The Associated Press, Axios and other major U.S. outlets.

A couple of them, though, told me they were puzzled by the reading package for the first session.

It consisted of a Harvard case study, which a participant shared with me, examining the coverage of Hunter Biden’s lost laptop in the final days of the 2020 campaign. The story had been pushed by aides and allies of then-President Donald J. Trump who tried to persuade journalists that the hard drive’s contents would reveal the corruption of the father.

The news media’s handling of that narrative provides “an instructive case study on the power of social media and news organizations to mitigate media manipulation campaigns,” according to the Shorenstein Center summary.

The Hunter Biden laptop saga sure is instructive about something. As you may recall, panicked Trump allies frantically dumped its contents onto the internet and into reporters’ inboxes, a trove that apparently included embarrassing images and emails purportedly from the candidate’s son showing that he had tried to trade on the family name. The big social media platforms, primed for a repeat of the WikiLeaks 2016 election shenanigans, reacted forcefully: Twitter blocked links to a New York Post story that tied Joe Biden to the emails without strong evidence (though Twitter quickly reversed that decision) and Facebook limited the spread of the Post story under its own “misinformation” policy.

But as it now appears, the story about the laptop was an old-fashioned, politically motivated dirty tricks campaign, and describing it with the word “misinformation” doesn’t add much to our understanding of what happened. While some of the emails purportedly on the laptop have since been called genuine by at least one recipient, the younger Mr. Biden has said he doesn’t know if the laptop in question was his. And the “media manipulation campaign” was a threadbare, 11th-hour effort to produce a late-campaign scandal, an attempt at an October Surprise that has been part of nearly every presidential campaign I’ve covered.

The Wall Street Journal, as I reported at the time , looked hard at the story. Unable to prove that Joe Biden had tried, as vice president, to change U.S. policy to enrich a family member, The Journal refused to tell it the way the Trump aides wanted, leaving that spin to the right-wing tabloids. What remained was a murky situation that is hard to call “misinformation,” even if some journalists and academics like the clarity of that label. The Journal’s role was, in fact, a pretty standard journalistic exercise, a blend of fact-finding and the sort of news judgment that has fallen a bit out of favor as journalists have found themselves chasing social media.

While some academics use the term carefully, “misinformation” in the case of the lost laptop was more or less synonymous with “material passed along by Trump aides.” And in that context, the phrase “media manipulation” refers to any attempt to shape news coverage by people whose politics you dislike. (Emily Dreyfuss, a fellow at the Technology and Social Change Project at the Shorenstein Center, told me that “media manipulation,” despite its sinister ring, is “not necessarily nefarious.”)

The focus on who’s saying something, and how they’re spreading their claims, can pretty quickly lead Silicon Valley engineers to slap the “misinformation” label on something that is, in plainer English, true.

Shorenstein’s research director, Joan Donovan, who is leading the program and raised its funding from the John S. and James L. Knight Foundation, said that the Hunter Biden case study was “designed to cause conversation — it’s not supposed to leave you resolved as a reader.”

Ms. Donovan, a force on Twitter and a longtime student of the shadiest corners of the internet, said she defines “misinformation” as “false information that’s being spread.” She strongly objected to my suggestion that the term lacks a precise meaning.

She added that, appearances aside, she doesn’t believe the word is merely a left-wing label for things that Democrats don’t like. Instead, she traces the modern practice of “disinformation” (that is, deliberate misinformation) to the anti-corporate activists the Yes Men, famous for hoaxed corporate announcements and other stunts, and the “culture jamming” of Adbusters. But their tools, she wrote, have been adopted by “foreign operatives, partisan pundits, white supremacists, violent misogynists, grifters and scammers.”

Ms. Donovan is among the scholars who have tried to unravel the knotty information tangle of contemporary politics. She’s currently a compulsive consumer of Steve Bannon’s influential podcast, “War Room.” Like many of the journalists and academics who study our chaotic media environment, she has zeroed in on the way that trolls and pranksters developed tactics for angering and tricking people online over the first half of the last decade, and how those people brought their tactics to the right-wing reactionary politics in the decade’s second half.

To the people paying close attention, this new world was riveting and dangerous — and it was maddening that outsiders couldn’t see what was happening. For these information scholars, widespread media manipulation seemed like the main event of recent years, the main driver of millions of people’s beliefs, and the main reason Mr. Trump and people like him won elections all over the world. But this perspective, while sometimes revelatory, may leave little space for other causes of political action, or for other types of political lies, like the U.S. government’s long deception on its progress in the war in Afghanistan.

What had been a niche preoccupation has now been adopted by people who have spent somewhat less time on 4chan than Ms. Donovan. The broadcaster Katie Couric recently led the Aspen Institute’s Commission on Information Disorder. I moderated a panel at Bloomberg’s New Economy Forum with a different, somewhat dental, label for the same set of issues, “truth decay.” (The RAND Corporation seems to have coined that one, though T Bone Burnett did release an album by that name in 1980.) There, an Australian senator, Sarah Hanson-Young, said she thought the biggest culprit in misleading her fellow citizens about climate change had been Rupert Murdoch’s News Corp — hardly a new issue, or one that needs a new name. The New York Post’s insistence that the emails prove President Biden’s corruption, and not just his son’s influence peddling, are part of the same partisan genre.

This hints at a weakness of the new focus on misinformation: It’s a technocratic solution to a problem that’s as much about politics as technology. The new social media-fueled right-wing populists lie a lot, and stretch the truth more. But as American reporters quizzing Donald Trump’s fans on camera discovered, his audience was often in on the joke. And many of the most offensive things he said weren’t necessarily lies — they were just deeply ugly to half the country, including most of the people running news organizations and universities.

It’s more comfortable to reckon with an information crisis — if there’s anything we’re good at, it’s information — than a political one. If only responsible journalists and technologists could explain how misguided Mr. Trump’s statements were, surely the citizenry would come around. But these well-meaning communications experts never quite understood that the people who liked him knew what was going on, laughed about it and voted for him despite, or perhaps even because of, the times he went “too far.”

Harper’s Magazine recently published a broadside against “Big Disinfo,” contending that the think tanks raising money to focus on the topic were offering a simple solution to a political crisis that defies easy explanation and exaggerating the power of Facebook in a way that, ultimately, served Facebook most of all. The author, Joseph Bernstein, argued that the journalists and academics who specialize in exposing instances of disinformation seem to believe they have a particular claim on truth. “However well-intentioned these professionals are, they don’t have special access to the fabric of reality,” he wrote.

In fact, I’ve found many of the people worrying about our information diets are reassuringly modest about how far the new field of misinformation studies is going to take us. Ms. Donovan calls it “a new field of data journalism,” but said she agreed that “this part of the field needs to get better at figuring out what’s true or false.” The Aspen report acknowledged “that in a free society there are no ‘arbiters of truth.’” They’re putting healthy new pressure on tech platforms to be transparent in how claims — true and false — spread.

The editor in chief of The Texas Tribune, Sewell Chan, one of the Harvard course’s participants, said he didn’t think the program had a political slant, adding that it “helped me understand the new forms of mischief making and lie peddling that have emerged.”

“That said, like the term ‘fake news,’ misinformation is a loaded and somewhat subjective term,” he said. “I’m more comfortable with precise descriptions.”

I also feel the push and pull of the information ecosystem in my own journalism, as well as the temptation to evaluate a claim by its formal qualities — who is saying it and why — rather than its substance. Last April, for instance, I tweeted about what I saw as the sneaky way that anti-China Republicans around Donald Trump were pushing the idea that Covid-19 had leaked from a lab. There were informational red flags galore. But media criticism (and I’m sorry you’ve gotten this far into a media column to read this) is skin-deep. Below the partisan shouting match was a more interesting scientific shouting match (which also made liberal use of the word “misinformation”). And the state of that story now is that scientists’ understanding of the origins of Covid-19 is evolving and hotly debated , and we’re not going to be able to resolve it on Twitter.

The story of tech platforms helping to spread falsehoods is still incredibly important, as is the work of identifying stealthy social media campaigns from Washington to, as my colleague Davey Alba recently reported, Nairobi . And the Covid-19 pandemic also gave everyone from Mark Zuckerberg to my colleagues at The New York Times a new sense of urgency about, for instance, communicating the seriousness of the pandemic and the safety of vaccines in a media landscape littered with false reports.

But politics isn’t a science. We don’t need to mystify the old-fashioned practice of news judgment with a new terminology. There’s a danger in adopting jargony new frameworks we haven’t really thought through. The job of reporters isn’t, ultimately, to put neat labels on the news. It’s to report out what’s actually happening, as messy and unsatisfying as that can be.

Ben Smith is the media columnist. He joined The Times in 2020 after eight years as founding editor in chief of BuzzFeed News. Before that, he covered politics for Politico, The New York Daily News, The New York Observer and The New York Sun. Email: [email protected] More about Ben Smith

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How to write a social media case study (with template)

Written by by Jenn Chen

Published on  October 10, 2019

Reading time  8 minutes

You’ve got a good number of social media clients under your belt and you feel fairly confident in your own service or product content marketing strategy. To attract new clients, you’ll tell them how you’ve tripled someone else’s engagement rates but how do they know this is true? Enter the case study.

Social media case studies are often used as part of a sales funnel: the potential client sees themselves in the case study and signs up because they want the same or better results. At Sprout, we use this strategy with our own case studies highlighting our customer’s successes.

Writing and publishing case studies is time intensive but straight forward. This guide will walk through how to create a social media case study for your business and highlight some examples.

What is a social media case study?

A case study is basically a long testimonial or review. Case studies commonly highlight what a business has achieved by using a social media service or strategy, and they illustrate how your company’s offerings help clients in a specific situation. Some case studies are written just to examine how a problem was solved or performance was improved from a general perspective. For this guide, we’ll be examining case studies that are focused on highlighting a company’s own products and services.

Case studies come in all content formats: long-form article, downloadable PDF, video and infographic. A single case study can be recycled into different formats as long as the information is still relevant.

At their core, case studies serve to inform a current or potential customer about a real-life scenario where your service or product was applied. There’s often a set date range for the campaign and accompanying, real-life statistics. The idea is to help the reader get a clearer understanding of how to use your product and why it could help.

Broad selling points like “our service will cut down your response time” are nice but a sentence like “After three months of using the software for responses, the company decreased their response time by 52%” works even better. It’s no longer a dream that you’ll help them decrease the response time because you already have with another company.

So now that you understand what a case study is, let’s get started on how to create one that’s effective and will help attract new clients.

How to write a social marketing case study

Writing an effective case study is all about the prep work. You’ve got to get all of the questions and set up ready so you can minimize lots of back and forth between you and the client.

1. Prepare your questions

Depending on how the case study will be presented and how familiar you are with the client to be featured, you may want to send some preliminary questions before the interview. It’s important to not only get permission from the company to use their logo, quotes and graphs but also to make sure they know they’ll be going into a public case study.

Your preliminary questions should cover background information about the company and ask about campaigns they are interested in discussing. Be sure to also identify which of your products and services they used. You can go into the details in the interview.

Once you receive the preliminary answers back, it’s time to prepare your questions for the interview. This is where you’ll get more information about how they used your products and how they contributed to the campaign’s success.

2. Interview

When you conduct your interview, think ahead on how you want it to be done. Whether it’s a phone call, video meeting or in-person meeting, you want to make sure it’s recorded. You can use tools like Google Meet, Zoom or UberConference to host and record calls (with your client’s permission, of course). This ensures that your quotes are accurate and you can play it back in case you miss any information. Tip: test out your recording device and process before the interview. You don’t want to go through the interview only to find out the recording didn’t save.

Ask open-ended questions to invite good quotes. You may need to use follow-up questions if the answers are too vague. Here are some examples.

• Explain how you use (your product or service) in general and for the campaign. Please name specific features.
• Describe how the feature helped your campaign achieve success.
• What were the campaign outcomes?
• What did you learn from the campaign?

Since we’re focused on creating a social media case study in this case, you can dive more deeply into social strategies and tactics too:

• Tell me about your approach to social media. How has it changed over time, if at all? What role does it play for the organization? How do you use it? What are you hoping to achieve?
• Are there specific social channels you prioritize? If so, why?
• How do you make sure your social efforts are reaching the right audience?
• What specific challenges do organizations like yours face when it comes to social?
• How do you measure the ROI of using social ? Are there certain outcomes that prove the value of social for your organization? What metrics are you using to determine how effective social is for you?

As the conversation continues, you can ask more leading questions if you need to to make sure you get quotes that tie these strategic insights directly back to the services, products or strategies your company has delivered to the client to help them achieve success. Here are just a couple of examples.

• Are there specific features that stick out to you as particularly helpful or especially beneficial for you and your objectives?
• How are you using (product/service) to support your social strategy? What’s a typical day like for your team using it?

The above quote was inserted into the Sprout Lake Metroparks case study . It’s an example of identifying a quote from an interview that helps make the impact of the product tangible in a client’s day to day.

At the end of the interview, be sure to thank the company and request relevant assets.

Afterwards, you may want to transcribe the interview to increase the ease of reviewing the material and writing the case study. You can DIY or use a paid service like Rev to speed up this part of the process.

3. Request assets and graphics

This is another important prep step because you want to make sure you get everything you need out of one request and avoid back and forth that takes up both you and your customer’s time. Be very clear on what you need and the file formats you need them in.

Some common assets include:

• Logo in .png format
• Logo guidelines so you know how to use them correctly
• Links to social media posts that were used during the campaign
• Headshots of people you interviewed
• Social media analytics reports. Make sure you name them and provide the requested date range, so that if you’re using a tool like Sprout, clients know which one to export.

4. Write the copy

Now that the information has been collected, it’s time to dissect it all and assemble it. At the end of this guide, we have an example outline template for you to follow. When writing a case study, you want to write to the audience that you’re trying to attract . In this case, it’ll be a potential customer that’s similar to the one you’re highlighting.

Use a mix of sentences and bullet points to attract different kinds of readers. The tone should be uplifting because you’re highlighting a success story. When identifying quotes to use, remove any fillers (“um”) and cut out unnecessary info.

5. Pay attention to formatting

And finally, depending on the content type, enlist the help of a graphic designer to make it look presentable. You may also want to include call-to-action buttons or links inside of your article. If you offer free trials, case studies are a great place to promote them.

Social media case study template

Writing a case study is a lot like writing a story or presenting a research paper (but less dry). This is a general outline to follow but you are welcome to enhance to fit your needs.

Headline Attention-grabbing and effective. Example: “ How Benefit turns cosmetics into connection using Sprout Social ” Summary A few sentences long with a basic overview of the brand’s story. Give the who, what, where, why and how. Which service and/or product did they use? Introduce the company Give background on who you’re highlighting. Include pertinent information like how big their social media team is, information about who you interviewed and how they run their social media. Describe the problem or campaign What were they trying to solve? Why was this a problem for them? What were the goals of the campaign? Present the solution and end results Describe what was done to achieve success. Include relevant social media statistics (graphics are encouraged). Conclusion Wrap it up with a reflection from the company spokesperson. How did they think the campaign went? What would they change to build on this success for the future? How did using the service compare to other services used in a similar situation?

Case studies are essential marketing and sales tools for any business that offer robust services or products. They help the customer reading them to picture their own company using the product in a similar fashion. Like a testimonial, words from the case study’s company carry more weight than sales points from the company.

When creating your first case study, keep in mind that preparation is the key to success. You want to find a company that is more than happy to sing your praises and share details about their social media campaign.

Once you’ve started developing case studies, find out the best ways to promote them alongside all your other content with our free social media content mix tool .

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Part of the book series: Sustainable Management, Wertschöpfung und Effizienz ((SMWE))

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The COVID-19 virus that has spread throughout the world since the beginning of 2020 brought disruptive changes at many levels, including demographic, economic, and social shifts. In the media environment, too, the pandemic brought unprecedented changes, with unprecedented media reporting on a single topic. The following case studies try to analyse how this infodemic spread throughout Europe and how it affected society as well as consumers and businesses.

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Starosta, K. (2022). Case Studies on Media Reporting and Media Influence During the COVID-19 Pandemic. In: Measuring the Impact of Online Media on Consumers, Businesses and Society. Sustainable Management, Wertschöpfung und Effizienz. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-36729-9_10

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Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID -19 Policies across the US States

Zhijing Jin , Zeyu Peng , Tejas Vaidhya , Bernhard Schoelkopf , Rada Mihalcea

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• Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States (Jin et al., Findings 2021)
• Zhijing Jin, Zeyu Peng, Tejas Vaidhya, Bernhard Schoelkopf, and Rada Mihalcea. 2021. Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States . In Findings of the Association for Computational Linguistics: EMNLP 2021 , pages 288–301, Punta Cana, Dominican Republic. Association for Computational Linguistics.

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20 Best Social Media Marketing Case Study Examples

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How would you like to read the best social media marketing case studies ever published?

More importantly, how would you like to copy the best practices in social media marketing that are based on real-world examples and not just theory?

Below, you’ll find a list of the top 20 social media case study examples along with the results and key findings. By studying these social media marketing studies and applying the lessons learned on your own accounts, you can hopefully achieve similar results.

Table of Contents

Social Media Case Study Examples

793,500+ impressions for semrush on twitter  – walker sands social media case study.

The case study shows how Walker Sands implemented a premium Twitter microcontent program for Semrush, a global leader in digital marketing software. Semrush needed a strategic social media marketing partner to help distinguish its brand from competitors, drive a higher engagement rate among its target audience, and build brand loyalty. In this case study, you’ll find out how the social strategy focused on three things: using humor, embedding the brand in trending conversations, and focusing on the audience’s interests over marketing messages. The result was an increase of more than 793,500 impressions, 34,800 engagements, and a 4.4% average engagement rate.

Viral Oreo Super Bowl Tweet  – Social Media Case Study

This is a popular case study to learn valuable insights for B2C marketing. During Super Bowl XLVII, the lights went out in the football stadium and the Oreo brand went viral with a single tweet that said “Power out? No problem. You can still dunk in the dark.” Read the historical account of that famous social media marketing moment from the people who lived through it so you can gather ideas on how to be better prepared for future social media campaigns that you can take advantage of in real-time.

Facebook Posting Strategy That Lead to 3X Reach & Engagement  – Buffer Social Media Case Study

In this social media case study example, you’ll find out how Buffer cut its Facebook posting frequency by 50% but increased the average weekly reach and engagement by 3X. Hint: The strategy had to do with creating fewer, better-quality posts, that were aimed at gaining higher engagement.

Achieving a 9 Million Audience by Automating Pinterest SEO  – Social Media Case Study

This is a good social media marketing case study for marketers who use Pinterest. Discover how Chillital went from 0 to 9 million engaged audience members and 268 million impressions. You’ll learn about the step-by-step research process of finding where your audience lives and breathes content, get a detailed analysis of how the author used Pinterest to generate brand awareness, and learn about using community-driven content promotion to scale social media results.

5X Increase In App Installs from TikTok  – Bumble Social Media Case Study

With the use of TikTok on the rise, social media case studies are now being shared about how to get the most value out of marketing on this platform. This one, in particular, is good to read because it explains how Bumble, a dating app, used TikTok more effectively by following the mantra, “Don’t Make Ads, Make TikToks”. This case study in social media marketing resulted in a 5X increase in app installs and a 64% decrease in cost-per-registration.

330% Increase In Reach for the Make a Wish Foundation – Disney Social Media Case Study

Check out this case study to find out how the Make-A-Wish Foundation increased its social media reach, audience, and engagement by partnering with Disney in a Share Your Ears campaign. The strategy was simple: ask people to take a photo of themselves wearing Mickey Mouse ears, post it on social media with the hashtag #ShareYouEars, and a $5 donation would be made to Make-A-Wish. The results were unbelievable with over 1.7 million posted photos and 420 million social media impressions. This led to a 15% audience increase on Facebook and a 13% audience increase on Instagram with a total increase of 330% in social media reach and a 554% increase in engagement during the campaign.

How 3 Schools Used Social Media Advertising to Increase Website Traffic & Applications – Social Media Case Study

This example includes three of the best social media case studies from Finalsite, a marketing agency for educational institutions. It shows the power of social media advertising to increase website traffic and enrollment. One case study, in particular, shows how a limited budget of $350 per month increased website sessions by 515%, more than 2,200 clicks on the apply button for a study abroad application, 2,419 views on the request information page, and 575 views on the application process page.

Client Case Studies – LYFE Marketing Social Media Case Study

LYFE Marketing is a social media management company that helps clients gain new customers, generate sales, and increase brand exposure online. This page includes several of its top social media marketing case studies along with the approach and key results from each campaign. It’s packed with screenshots of the social media posts and engagement metrics so you can understand how each strategy worked for success, and get inspiration for your own campaigns.

3X Leads for a Local Business – Vertex Marketing Social Media Case Study

This is a good case study about finding the right balance between organic reach with social media posts and paid reach with social media marketing ads. You’ll find out how Vertex Marketing helped a local kitchen and bath remodeling business increase the number of leads by 3X. As for the return on investment (ROI) for this campaign, each lead for the client was worth about $10,000. The result was 6,628 audience reach, $12.43 average cost per conversion, and 18 conversions.

235% Increase In Conversions with Facebook Ads Funnel – Marketing 360 Social Media Case Study

This is one of Marketing 360’s case study examples that demonstrates the effectiveness of a Facebook ads sales funnel for B2B marketing. An ads funnel is a series of social media advertisements that target a specific audience at each stage of the buyer’s journey. By mapping out the buyer’s journey and creating a social media marketing ad campaign for each stage, you can guide new leads through the sales funnel and turn them into paying customers. This case study resulted in a 235% increase in conversions for a truck lift manufacturer.

15% Increase In Social Media Followers In 6 Months – Hootsuite Social Media Case Study

This is one of the best social media marketing case studies available online for businesses in the hospitality industry. Find out how Meliá Hotels International incorporated social media directly into its business model, both as a channel for client communication and as a platform to listen and learn about client needs and preferences. As a result, Meliá Hotel’s social media following grew from 5 million to 6 million in six months; an increase of more than 15%.

The Impact of Social Signals On SEO – Fat Stacks Social Media Case Study

This is a good case study for understanding the effect social media can have on SEO. By building links for a web page on social media channels like Facebook, Twitter, Pinterest, LinkedIn, etc, the rankings for long tail keywords improved in Google’s search engine.

96 Link Clicks for a Vacation Rental – Maria Peagler Social Media Case Study

As the title of this social media case study example suggests, you’ll learn how Maria Peagler helped a vacation rental get 96 clicks out of 3,274 audience reach on a single Facebook ad; about a 2.9% click-through rate (CTR). What’s most important about this B2C example is those clicks were of the highest quality the client could receive because Maria dug into the analytics to find out the best time during the day to post the ad and the perfect age groups to target while also using specific language to only drive clicks that would more likely convert.

Vienna Tourist Board Uses an Instagram Wall to Attract Tourists – Walls.io Social Media Case Study

Inside this case study, you’ll find out how the City of Vienna uses a simple social media content aggregator to display its Instagram feed on the website. This basic marketing strategy harnesses the power of user-generated content to gain more followers and keep in touch with previous visitors to increase brand awareness and repeat visits.

Complete Instagram Marketing Strategy for Sixthreezero – Vulpine Interactive Social Media Case Study

This is an in-depth case study on social media marketing with Instagram. You’ll discover how Vulpine Interactive was able to turn an existing, unmanaged account into a strong company asset for Sixthreezero, a bicycling company that uses ecommerce to drive sales. There was a lot of strategy and planning that went into growing the account by 39%, increasing website traffic from Instagram by over 300%, and achieving 77,659 total engagements. Inside, you’ll get the complete social strategy, tactics, key performance indicators (KPIs), and results

Twitter Marketing Success Stories – Social Media Case Study

If you’re looking for social media case study examples for Twitter using both organic and paid ads, then this page has everything you need. It includes Twitter’s top marketing success stories for you to get new ideas for your own B2C and B2B marketing campaigns.

How 3 Big Brands Use Pinterest for Marketing – SmartInsights Social Media Case Study

This is a case study page by SmartInsights with an overview of how 3 big brands use Pinterest for marketing. Although it’s a quick read, you can learn some valuable tactics that Nordstrom, Sephora, and Petplan are using to market their brands on this social media platform.

25+ TikTok Social Campaign Results – Chatdesk Social Media Case Study

If you’re looking for the best social media case studies for TikTok, then this list by Chatdesk is an excellent resource. It includes more than 25 examples from big brands like Starbucks, Redbull, Spikeball, Crocs, Guess Jeans, and Gym Shark. Give it a read to find out exactly how these brands use TikTok effectively to scale their businesses.

Reddit for Business: Meet Your Maker – Social Media Case Study

Want to learn how to use Reddit to market your business online? This new social media marketing case study page by Reddit called “Meet Your Maker” showcases the people behind some of the most innovative and creative brand activations on our platform. Examples include campaigns by Adobe, Capcom, and noosa Yoghurt.

How Boston University Uses Snapchat to Engage with Students – Social Media Case Study

With more than 75% of college students using Snapchat on a daily basis, it became clear that Boston University had to make this platform a primary marketing channel. This social media case study outlines all of the top strategies Boston University uses to connect with prospective and current students.

Now, if you’re looking for more digital marketing ideas, then make sure to check out these other related guides:  SEO case studies with data on improving organic search engine optimization, PPC case studies  for paid search examples, email marketing case studies , affiliate marketing case studies , content marketing case studies , and general digital marketing case studies .

What Is a Social Media Case Study?

A social media case study is an in-depth study of social media marketing in a real-world context. It can focus on one social media tactic or a group of social media strategies to find out what works in social media marketing to promote a product or service.

Are Case Studies Good for Social Media Marketing?

Case studies are good for social media because you can learn about how to do social media marketing in an effective way. Instead of just studying the theory of social media, you can learn from real examples that applied social media marketing methods to achieve success.

Summary for Social Media Marketing Case Studies

I hope you enjoyed this list of the best social media marketing case study examples that are based on real-world results and not just theory.

As you discovered, the social media case studies above demonstrated many different ways to perform well on social platforms. By studying the key findings from these case study examples, and applying the methods learned to your own accounts, you can hopefully achieve the same positive outcome. New social media case studies are being published every month and I’ll continue to update this list as they become available. So keep checking back to read the current sources of information on social media.

Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

• Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
• Fifty four percent of raw case users came from outside the U.S..
• The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
• Twenty-six of the cases in the list are raw cases.
• A third of the cases feature a woman protagonist.
• Orders for Yale SOM case studies increased by almost 50% compared to 2020.
• The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

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Fake news, disinformation and misinformation in social media: a review

Esma aïmeur.

Department of Computer Science and Operations Research (DIRO), University of Montreal, Montreal, Canada

Sabrine Amri

Gilles brassard, associated data.

All the data and material are available in the papers cited in the references.

Online social networks (OSNs) are rapidly growing and have become a huge source of all kinds of global and local news for millions of users. However, OSNs are a double-edged sword. Although the great advantages they offer such as unlimited easy communication and instant news and information, they can also have many disadvantages and issues. One of their major challenging issues is the spread of fake news. Fake news identification is still a complex unresolved issue. Furthermore, fake news detection on OSNs presents unique characteristics and challenges that make finding a solution anything but trivial. On the other hand, artificial intelligence (AI) approaches are still incapable of overcoming this challenging problem. To make matters worse, AI techniques such as machine learning and deep learning are leveraged to deceive people by creating and disseminating fake content. Consequently, automatic fake news detection remains a huge challenge, primarily because the content is designed in a way to closely resemble the truth, and it is often hard to determine its veracity by AI alone without additional information from third parties. This work aims to provide a comprehensive and systematic review of fake news research as well as a fundamental review of existing approaches used to detect and prevent fake news from spreading via OSNs. We present the research problem and the existing challenges, discuss the state of the art in existing approaches for fake news detection, and point out the future research directions in tackling the challenges.

Introduction

Context and motivation.

Fake news, disinformation and misinformation have become such a scourge that Marcia McNutt, president of the National Academy of Sciences of the United States, is quoted to have said (making an implicit reference to the COVID-19 pandemic) “Misinformation is worse than an epidemic: It spreads at the speed of light throughout the globe and can prove deadly when it reinforces misplaced personal bias against all trustworthy evidence” in a joint statement of the National Academies 1 posted on July 15, 2021. Indeed, although online social networks (OSNs), also called social media, have improved the ease with which real-time information is broadcast; its popularity and its massive use have expanded the spread of fake news by increasing the speed and scope at which it can spread. Fake news may refer to the manipulation of information that can be carried out through the production of false information, or the distortion of true information. However, that does not mean that this problem is only created with social media. A long time ago, there were rumors in the traditional media that Elvis was not dead, 2 that the Earth was flat, 3 that aliens had invaded us, 4 , etc.

Therefore, social media has become nowadays a powerful source for fake news dissemination (Sharma et al. 2019 ; Shu et al. 2017 ). According to Pew Research Center’s analysis of the news use across social media platforms, in 2020, about half of American adults get news on social media at least sometimes, 5 while in 2018, only one-fifth of them say they often get news via social media. 6

Hence, fake news can have a significant impact on society as manipulated and false content is easier to generate and harder to detect (Kumar and Shah 2018 ) and as disinformation actors change their tactics (Kumar and Shah 2018 ; Micallef et al. 2020 ). In 2017, Snow predicted in the MIT Technology Review (Snow 2017 ) that most individuals in mature economies will consume more false than valid information by 2022.

Recent news on the COVID-19 pandemic, which has flooded the web and created panic in many countries, has been reported as fake. 7 For example, holding your breath for ten seconds to one minute is not a self-test for COVID-19 8 (see Fig.  1 ). Similarly, online posts claiming to reveal various “cures” for COVID-19 such as eating boiled garlic or drinking chlorine dioxide (which is an industrial bleach), were verified 9 as fake and in some cases as dangerous and will never cure the infection.

Fake news example about a self-test for COVID-19 source: https://cdn.factcheck.org/UploadedFiles/Screenshot031120_false.jpg , last access date: 26-12-2022

Social media outperformed television as the major news source for young people of the UK and the USA. 10 Moreover, as it is easier to generate and disseminate news online than with traditional media or face to face, large volumes of fake news are produced online for many reasons (Shu et al. 2017 ). Furthermore, it has been reported in a previous study about the spread of online news on Twitter (Vosoughi et al. 2018 ) that the spread of false news online is six times faster than truthful content and that 70% of the users could not distinguish real from fake news (Vosoughi et al. 2018 ) due to the attraction of the novelty of the latter (Bovet and Makse 2019 ). It was determined that falsehood spreads significantly farther, faster, deeper and more broadly than the truth in all categories of information, and the effects are more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information (Vosoughi et al. 2018 ).

Over 1 million tweets were estimated to be related to fake news by the end of the 2016 US presidential election. 11 In 2017, in Germany, a government spokesman affirmed: “We are dealing with a phenomenon of a dimension that we have not seen before,” referring to an unprecedented spread of fake news on social networks. 12 Given the strength of this new phenomenon, fake news has been chosen as the word of the year by the Macquarie dictionary both in 2016 13 and in 2018 14 as well as by the Collins dictionary in 2017. 15 , 16 Since 2020, the new term “infodemic” was coined, reflecting widespread researchers’ concern (Gupta et al. 2022 ; Apuke and Omar 2021 ; Sharma et al. 2020 ; Hartley and Vu 2020 ; Micallef et al. 2020 ) about the proliferation of misinformation linked to the COVID-19 pandemic.

The Gartner Group’s top strategic predictions for 2018 and beyond included the need for IT leaders to quickly develop Artificial Intelligence (AI) algorithms to address counterfeit reality and fake news. 17 However, fake news identification is a complex issue. (Snow 2017 ) questioned the ability of AI to win the war against fake news. Similarly, other researchers concurred that even the best AI for spotting fake news is still ineffective. 18 Besides, recent studies have shown that the power of AI algorithms for identifying fake news is lower than its ability to create it Paschen ( 2019 ). Consequently, automatic fake news detection remains a huge challenge, primarily because the content is designed to closely resemble the truth in order to deceive users, and as a result, it is often hard to determine its veracity by AI alone. Therefore, it is crucial to consider more effective approaches to solve the problem of fake news in social media.

Contribution

The fake news problem has been addressed by researchers from various perspectives related to different topics. These topics include, but are not restricted to, social science studies , which investigate why and who falls for fake news (Altay et al. 2022 ; Batailler et al. 2022 ; Sterret et al. 2018 ; Badawy et al. 2019 ; Pennycook and Rand 2020 ; Weiss et al. 2020 ; Guadagno and Guttieri 2021 ), whom to trust and how perceptions of misinformation and disinformation relate to media trust and media consumption patterns (Hameleers et al. 2022 ), how fake news differs from personal lies (Chiu and Oh 2021 ; Escolà-Gascón 2021 ), examine how can the law regulate digital disinformation and how governments can regulate the values of social media companies that themselves regulate disinformation spread on their platforms (Marsden et al. 2020 ; Schuyler 2019 ; Vasu et al. 2018 ; Burshtein 2017 ; Waldman 2017 ; Alemanno 2018 ; Verstraete et al. 2017 ), and argue the challenges to democracy (Jungherr and Schroeder 2021 ); Behavioral interventions studies , which examine what literacy ideas mean in the age of dis/mis- and malinformation (Carmi et al. 2020 ), investigate whether media literacy helps identification of fake news (Jones-Jang et al. 2021 ) and attempt to improve people’s news literacy (Apuke et al. 2022 ; Dame Adjin-Tettey 2022 ; Hameleers 2022 ; Nagel 2022 ; Jones-Jang et al. 2021 ; Mihailidis and Viotty 2017 ; García et al. 2020 ) by encouraging people to pause to assess credibility of headlines (Fazio 2020 ), promote civic online reasoning (McGrew 2020 ; McGrew et al. 2018 ) and critical thinking (Lutzke et al. 2019 ), together with evaluations of credibility indicators (Bhuiyan et al. 2020 ; Nygren et al. 2019 ; Shao et al. 2018a ; Pennycook et al. 2020a , b ; Clayton et al. 2020 ; Ozturk et al. 2015 ; Metzger et al. 2020 ; Sherman et al. 2020 ; Nekmat 2020 ; Brashier et al. 2021 ; Chung and Kim 2021 ; Lanius et al. 2021 ); as well as social media-driven studies , which investigate the effect of signals (e.g., sources) to detect and recognize fake news (Vraga and Bode 2017 ; Jakesch et al. 2019 ; Shen et al. 2019 ; Avram et al. 2020 ; Hameleers et al. 2020 ; Dias et al. 2020 ; Nyhan et al. 2020 ; Bode and Vraga 2015 ; Tsang 2020 ; Vishwakarma et al. 2019 ; Yavary et al. 2020 ) and investigate fake and reliable news sources using complex networks analysis based on search engine optimization metric (Mazzeo and Rapisarda 2022 ).

The impacts of fake news have reached various areas and disciplines beyond online social networks and society (García et al. 2020 ) such as economics (Clarke et al. 2020 ; Kogan et al. 2019 ; Goldstein and Yang 2019 ), psychology (Roozenbeek et al. 2020a ; Van der Linden and Roozenbeek 2020 ; Roozenbeek and van der Linden 2019 ), political science (Valenzuela et al. 2022 ; Bringula et al. 2022 ; Ricard and Medeiros 2020 ; Van der Linden et al. 2020 ; Allcott and Gentzkow 2017 ; Grinberg et al. 2019 ; Guess et al. 2019 ; Baptista and Gradim 2020 ), health science (Alonso-Galbán and Alemañy-Castilla 2022 ; Desai et al. 2022 ; Apuke and Omar 2021 ; Escolà-Gascón 2021 ; Wang et al. 2019c ; Hartley and Vu 2020 ; Micallef et al. 2020 ; Pennycook et al. 2020b ; Sharma et al. 2020 ; Roozenbeek et al. 2020b ), environmental science (e.g., climate change) (Treen et al. 2020 ; Lutzke et al. 2019 ; Lewandowsky 2020 ; Maertens et al. 2020 ), etc.

Interesting research has been carried out to review and study the fake news issue in online social networks. Some focus not only on fake news, but also distinguish between fake news and rumor (Bondielli and Marcelloni 2019 ; Meel and Vishwakarma 2020 ), while others tackle the whole problem, from characterization to processing techniques (Shu et al. 2017 ; Guo et al. 2020 ; Zhou and Zafarani 2020 ). However, they mostly focus on studying approaches from a machine learning perspective (Bondielli and Marcelloni 2019 ), data mining perspective (Shu et al. 2017 ), crowd intelligence perspective (Guo et al. 2020 ), or knowledge-based perspective (Zhou and Zafarani 2020 ). Furthermore, most of these studies ignore at least one of the mentioned perspectives, and in many cases, they do not cover other existing detection approaches using methods such as blockchain and fact-checking, as well as analysis on metrics used for Search Engine Optimization (Mazzeo and Rapisarda 2022 ). However, in our work and to the best of our knowledge, we cover all the approaches used for fake news detection. Indeed, we investigate the proposed solutions from broader perspectives (i.e., the detection techniques that are used, as well as the different aspects and types of the information used).

Therefore, in this paper, we are highly motivated by the following facts. First, fake news detection on social media is still in the early age of development, and many challenging issues remain that require deeper investigation. Hence, it is necessary to discuss potential research directions that can improve fake news detection and mitigation tasks. However, the dynamic nature of fake news propagation through social networks further complicates matters (Sharma et al. 2019 ). False information can easily reach and impact a large number of users in a short time (Friggeri et al. 2014 ; Qian et al. 2018 ). Moreover, fact-checking organizations cannot keep up with the dynamics of propagation as they require human verification, which can hold back a timely and cost-effective response (Kim et al. 2018 ; Ruchansky et al. 2017 ; Shu et al. 2018a ).

Our work focuses primarily on understanding the “fake news” problem, its related challenges and root causes, and reviewing automatic fake news detection and mitigation methods in online social networks as addressed by researchers. The main contributions that differentiate us from other works are summarized below:

• We present the general context from which the fake news problem emerged (i.e., online deception)
• We review existing definitions of fake news, identify the terms and features most commonly used to define fake news, and categorize related works accordingly.
• We propose a fake news typology classification based on the various categorizations of fake news reported in the literature.
• We point out the most challenging factors preventing researchers from proposing highly effective solutions for automatic fake news detection in social media.
• We highlight and classify representative studies in the domain of automatic fake news detection and mitigation on online social networks including the key methods and techniques used to generate detection models.
• We discuss the key shortcomings that may inhibit the effectiveness of the proposed fake news detection methods in online social networks.
• We provide recommendations that can help address these shortcomings and improve the quality of research in this domain.

The rest of this article is organized as follows. We explain the methodology with which the studied references are collected and selected in Sect.  2 . We introduce the online deception problem in Sect.  3 . We highlight the modern-day problem of fake news in Sect.  4 , followed by challenges facing fake news detection and mitigation tasks in Sect.  5 . We provide a comprehensive literature review of the most relevant scholarly works on fake news detection in Sect.  6 . We provide a critical discussion and recommendations that may fill some of the gaps we have identified, as well as a classification of the reviewed automatic fake news detection approaches, in Sect.  7 . Finally, we provide a conclusion and propose some future directions in Sect.  8 .

Review methodology

This section introduces the systematic review methodology on which we relied to perform our study. We start with the formulation of the research questions, which allowed us to select the relevant research literature. Then, we provide the different sources of information together with the search and inclusion/exclusion criteria we used to select the final set of papers.

Research questions formulation

The research scope, research questions, and inclusion/exclusion criteria were established following an initial evaluation of the literature and the following research questions were formulated and addressed.

• RQ1: what is fake news in social media, how is it defined in the literature, what are its related concepts, and the different types of it?
• RQ2: What are the existing challenges and issues related to fake news?
• RQ3: What are the available techniques used to perform fake news detection in social media?

Sources of information

We broadly searched for journal and conference research articles, books, and magazines as a source of data to extract relevant articles. We used the main sources of scientific databases and digital libraries in our search, such as Google Scholar, 19 IEEE Xplore, 20 Springer Link, 21 ScienceDirect, 22 Scopus, 23 ACM Digital Library. 24 Also, we screened most of the related high-profile conferences such as WWW, SIGKDD, VLDB, ICDE and so on to find out the recent work.

Search criteria

We focused our research over a period of ten years, but we made sure that about two-thirds of the research papers that we considered were published in or after 2019. Additionally, we defined a set of keywords to search the above-mentioned scientific databases since we concentrated on reviewing the current state of the art in addition to the challenges and the future direction. The set of keywords includes the following terms: fake news, disinformation, misinformation, information disorder, social media, detection techniques, detection methods, survey, literature review.

Study selection, exclusion and inclusion criteria

To retrieve relevant research articles, based on our sources of information and search criteria, a systematic keyword-based search was carried out by posing different search queries, as shown in Table  1 .

List of keywords for searching relevant articles

We discovered a primary list of articles. On the obtained initial list of studies, we applied a set of inclusion/exclusion criteria presented in Table  2 to select the appropriate research papers. The inclusion and exclusion principles are applied to determine whether a study should be included or not.

Inclusion and exclusion criteria

After reading the abstract, we excluded some articles that did not meet our criteria. We chose the most important research to help us understand the field. We reviewed the articles completely and found only 61 research papers that discuss the definition of the term fake news and its related concepts (see Table  4 ). We used the remaining papers to understand the field, reveal the challenges, review the detection techniques, and discuss future directions.

Classification of fake news definitions based on the used term and features

A brief introduction of online deception

The Cambridge Online Dictionary defines Deception as “ the act of hiding the truth, especially to get an advantage .” Deception relies on peoples’ trust, doubt and strong emotions that may prevent them from thinking and acting clearly (Aïmeur et al. 2018 ). We also define it in previous work (Aïmeur et al. 2018 ) as the process that undermines the ability to consciously make decisions and take convenient actions, following personal values and boundaries. In other words, deception gets people to do things they would not otherwise do. In the context of online deception, several factors need to be considered: the deceiver, the purpose or aim of the deception, the social media service, the deception technique and the potential target (Aïmeur et al. 2018 ; Hage et al. 2021 ).

Researchers are working on developing new ways to protect users and prevent online deception (Aïmeur et al. 2018 ). Due to the sophistication of attacks, this is a complex task. Hence, malicious attackers are using more complex tools and strategies to deceive users. Furthermore, the way information is organized and exchanged in social media may lead to exposing OSN users to many risks (Aïmeur et al. 2013 ).

In fact, this field is one of the recent research areas that need collaborative efforts of multidisciplinary practices such as psychology, sociology, journalism, computer science as well as cyber-security and digital marketing (which are not yet well explored in the field of dis/mis/malinformation but relevant for future research). Moreover, Ismailov et al. ( 2020 ) analyzed the main causes that could be responsible for the efficiency gap between laboratory results and real-world implementations.

In this paper, it is not in our scope of work to review online deception state of the art. However, we think it is crucial to note that fake news, misinformation and disinformation are indeed parts of the larger landscape of online deception (Hage et al. 2021 ).

Fake news, the modern-day problem

Fake news has existed for a very long time, much before their wide circulation became facilitated by the invention of the printing press. 25 For instance, Socrates was condemned to death more than twenty-five hundred years ago under the fake news that he was guilty of impiety against the pantheon of Athens and corruption of the youth. 26 A Google Trends Analysis of the term “fake news” reveals an explosion in popularity around the time of the 2016 US presidential election. 27 Fake news detection is a problem that has recently been addressed by numerous organizations, including the European Union 28 and NATO. 29

In this section, we first overview the fake news definitions as they were provided in the literature. We identify the terms and features used in the definitions, and we classify the latter based on them. Then, we provide a fake news typology based on distinct categorizations that we propose, and we define and compare the most cited forms of one specific fake news category (i.e., the intent-based fake news category).

Definitions of fake news

“Fake news” is defined in the Collins English Dictionary as false and often sensational information disseminated under the guise of news reporting, 30 yet the term has evolved over time and has become synonymous with the spread of false information (Cooke 2017 ).

The first definition of the term fake news was provided by Allcott and Gentzkow ( 2017 ) as news articles that are intentionally and verifiably false and could mislead readers. Then, other definitions were provided in the literature, but they all agree on the authenticity of fake news to be false (i.e., being non-factual). However, they disagree on the inclusion and exclusion of some related concepts such as satire , rumors , conspiracy theories , misinformation and hoaxes from the given definition. More recently, Nakov ( 2020 ) reported that the term fake news started to mean different things to different people, and for some politicians, it even means “news that I do not like.”

Hence, there is still no agreed definition of the term “fake news.” Moreover, we can find many terms and concepts in the literature that refer to fake news (Van der Linden et al. 2020 ; Molina et al. 2021 ) (Abu Arqoub et al. 2022 ; Allen et al. 2020 ; Allcott and Gentzkow 2017 ; Shu et al. 2017 ; Sharma et al. 2019 ; Zhou and Zafarani 2020 ; Zhang and Ghorbani 2020 ; Conroy et al. 2015 ; Celliers and Hattingh 2020 ; Nakov 2020 ; Shu et al. 2020c ; Jin et al. 2016 ; Rubin et al. 2016 ; Balmas 2014 ; Brewer et al. 2013 ; Egelhofer and Lecheler 2019 ; Mustafaraj and Metaxas 2017 ; Klein and Wueller 2017 ; Potthast et al. 2017 ; Lazer et al. 2018 ; Weiss et al. 2020 ; Tandoc Jr et al. 2021 ; Guadagno and Guttieri 2021 ), disinformation (Kapantai et al. 2021 ; Shu et al. 2020a , c ; Kumar et al. 2016 ; Bhattacharjee et al. 2020 ; Marsden et al. 2020 ; Jungherr and Schroeder 2021 ; Starbird et al. 2019 ; Ireton and Posetti 2018 ), misinformation (Wu et al. 2019 ; Shu et al. 2020c ; Shao et al. 2016 , 2018b ; Pennycook and Rand 2019 ; Micallef et al. 2020 ), malinformation (Dame Adjin-Tettey 2022 ) (Carmi et al. 2020 ; Shu et al. 2020c ), false information (Kumar and Shah 2018 ; Guo et al. 2020 ; Habib et al. 2019 ), information disorder (Shu et al. 2020c ; Wardle and Derakhshan 2017 ; Wardle 2018 ; Derakhshan and Wardle 2017 ), information warfare (Guadagno and Guttieri 2021 ) and information pollution (Meel and Vishwakarma 2020 ).

There is also a remarkable amount of disagreement over the classification of the term fake news in the research literature, as well as in policy (de Cock Buning 2018 ; ERGA 2018 , 2021 ). Some consider fake news as a type of misinformation (Allen et al. 2020 ; Singh et al. 2021 ; Ha et al. 2021 ; Pennycook and Rand 2019 ; Shao et al. 2018b ; Di Domenico et al. 2021 ; Sharma et al. 2019 ; Celliers and Hattingh 2020 ; Klein and Wueller 2017 ; Potthast et al. 2017 ; Islam et al. 2020 ), others consider it as a type of disinformation (de Cock Buning 2018 ) (Bringula et al. 2022 ; Baptista and Gradim 2022 ; Tsang 2020 ; Tandoc Jr et al. 2021 ; Bastick 2021 ; Khan et al. 2019 ; Shu et al. 2017 ; Nakov 2020 ; Shu et al. 2020c ; Egelhofer and Lecheler 2019 ), while others associate the term with both disinformation and misinformation (Wu et al. 2022 ; Dame Adjin-Tettey 2022 ; Hameleers et al. 2022 ; Carmi et al. 2020 ; Allcott and Gentzkow 2017 ; Zhang and Ghorbani 2020 ; Potthast et al. 2017 ; Weiss et al. 2020 ; Tandoc Jr et al. 2021 ; Guadagno and Guttieri 2021 ). On the other hand, some prefer to differentiate fake news from both terms (ERGA 2018 ; Molina et al. 2021 ; ERGA 2021 ) (Zhou and Zafarani 2020 ; Jin et al. 2016 ; Rubin et al. 2016 ; Balmas 2014 ; Brewer et al. 2013 ).

The existing terms can be separated into two groups. The first group represents the general terms, which are information disorder , false information and fake news , each of which includes a subset of terms from the second group. The second group represents the elementary terms, which are misinformation , disinformation and malinformation . The literature agrees on the definitions of the latter group, but there is still no agreed-upon definition of the first group. In Fig.  2 , we model the relationship between the most used terms in the literature.

Modeling of the relationship between terms related to fake news

The terms most used in the literature to refer, categorize and classify fake news can be summarized and defined as shown in Table  3 , in which we capture the similarities and show the differences between the different terms based on two common key features, which are the intent and the authenticity of the news content. The intent feature refers to the intention behind the term that is used (i.e., whether or not the purpose is to mislead or cause harm), whereas the authenticity feature refers to its factual aspect. (i.e., whether the content is verifiably false or not, which we label as genuine in the second case). Some of these terms are explicitly used to refer to fake news (i.e., disinformation, misinformation and false information), while others are not (i.e., malinformation). In the comparison table, the empty dash (–) cell denotes that the classification does not apply.

A comparison between used terms based on intent and authenticity

In Fig.  3 , we identify the different features used in the literature to define fake news (i.e., intent, authenticity and knowledge). Hence, some definitions are based on two key features, which are authenticity and intent (i.e., news articles that are intentionally and verifiably false and could mislead readers). However, other definitions are based on either authenticity or intent. Other researchers categorize false information on the web and social media based on its intent and knowledge (i.e., when there is a single ground truth). In Table  4 , we classify the existing fake news definitions based on the used term and the used features . In the classification, the references in the cells refer to the research study in which a fake news definition was provided, while the empty dash (–) cells denote that the classification does not apply.

The features used for fake news definition

Fake news typology

Various categorizations of fake news have been provided in the literature. We can distinguish two major categories of fake news based on the studied perspective (i.e., intention or content) as shown in Fig.  4 . However, our proposed fake news typology is not about detection methods, and it is not exclusive. Hence, a given category of fake news can be described based on both perspectives (i.e., intention and content) at the same time. For instance, satire (i.e., intent-based fake news) can contain text and/or multimedia content types of data (e.g., headline, body, image, video) (i.e., content-based fake news) and so on.

Most researchers classify fake news based on the intent (Collins et al. 2020 ; Bondielli and Marcelloni 2019 ; Zannettou et al. 2019 ; Kumar et al. 2016 ; Wardle 2017 ; Shu et al. 2017 ; Kumar and Shah 2018 ) (see Sect.  4.2.2 ). However, other researchers (Parikh and Atrey 2018 ; Fraga-Lamas and Fernández-Caramés 2020 ; Hasan and Salah 2019 ; Masciari et al. 2020 ; Bakdash et al. 2018 ; Elhadad et al. 2019 ; Yang et al. 2019b ) focus on the content to categorize types of fake news through distinguishing the different formats and content types of data in the news (e.g., text and/or multimedia).

Recently, another classification was proposed by Zhang and Ghorbani ( 2020 ). It is based on the combination of content and intent to categorize fake news. They distinguish physical news content and non-physical news content from fake news. Physical content consists of the carriers and format of the news, and non-physical content consists of the opinions, emotions, attitudes and sentiments that the news creators want to express.

Content-based fake news category

According to researchers of this category (Parikh and Atrey 2018 ; Fraga-Lamas and Fernández-Caramés 2020 ; Hasan and Salah 2019 ; Masciari et al. 2020 ; Bakdash et al. 2018 ; Elhadad et al. 2019 ; Yang et al. 2019b ), forms of fake news may include false text such as hyperlinks or embedded content; multimedia such as false videos (Demuyakor and Opata 2022 ), images (Masciari et al. 2020 ; Shen et al. 2019 ), audios (Demuyakor and Opata 2022 ) and so on. Moreover, we can also find multimodal content (Shu et al. 2020a ) that is fake news articles and posts composed of multiple types of data combined together, for example, a fabricated image along with a text related to the image (Shu et al. 2020a ). In this category of fake news forms, we can mention as examples deepfake videos (Yang et al. 2019b ) and GAN-generated fake images (Zhang et al. 2019b ), which are artificial intelligence-based machine-generated fake content that are hard for unsophisticated social network users to identify.

The effects of these forms of fake news content vary on the credibility assessment, as well as sharing intentions which influences the spread of fake news on OSNs. For instance, people with little knowledge about the issue compared to those who are strongly concerned about the key issue of fake news tend to be easier to convince that the misleading or fake news is real, especially when shared via a video modality as compared to the text or the audio modality (Demuyakor and Opata 2022 ).

Intent-based Fake News Category

The most often mentioned and discussed forms of fake news according to researchers in this category include but are not restricted to clickbait , hoax , rumor , satire , propaganda , framing , conspiracy theories and others. In the following subsections, we explain these types of fake news as they were defined in the literature and undertake a brief comparison between them as depicted in Table  5 . The following are the most cited forms of intent-based types of fake news, and their comparison is based on what we suspect are the most common criteria mentioned by researchers.

A comparison between the different types of intent-based fake news

Clickbait refers to misleading headlines and thumbnails of content on the web (Zannettou et al. 2019 ) that tend to be fake stories with catchy headlines aimed at enticing the reader to click on a link (Collins et al. 2020 ). This type of fake news is considered to be the least severe type of false information because if a user reads/views the whole content, it is possible to distinguish if the headline and/or the thumbnail was misleading (Zannettou et al. 2019 ). However, the goal behind using clickbait is to increase the traffic to a website (Zannettou et al. 2019 ).

A hoax is a false (Zubiaga et al. 2018 ) or inaccurate (Zannettou et al. 2019 ) intentionally fabricated (Collins et al. 2020 ) news story used to masquerade the truth (Zubiaga et al. 2018 ) and is presented as factual (Zannettou et al. 2019 ) to deceive the public or audiences (Collins et al. 2020 ). This category is also known either as half-truth or factoid stories (Zannettou et al. 2019 ). Popular examples of hoaxes are stories that report the false death of celebrities (Zannettou et al. 2019 ) and public figures (Collins et al. 2020 ). Recently, hoaxes about the COVID-19 have been circulating through social media.

The term rumor refers to ambiguous or never confirmed claims (Zannettou et al. 2019 ) that are disseminated with a lack of evidence to support them (Sharma et al. 2019 ). This kind of information is widely propagated on OSNs (Zannettou et al. 2019 ). However, they are not necessarily false and may turn out to be true (Zubiaga et al. 2018 ). Rumors originate from unverified sources but may be true or false or remain unresolved (Zubiaga et al. 2018 ).

Satire refers to stories that contain a lot of irony and humor (Zannettou et al. 2019 ). It presents stories as news that might be factually incorrect, but the intent is not to deceive but rather to call out, ridicule, or to expose behavior that is shameful, corrupt, or otherwise “bad” (Golbeck et al. 2018 ). This is done with a fabricated story or by exaggerating the truth reported in mainstream media in the form of comedy (Collins et al. 2020 ). The intent behind satire seems kind of legitimate and many authors (such as Wardle (Wardle 2017 )) do include satire as a type of fake news as there is no intention to cause harm but it has the potential to mislead or fool people.

Also, Golbeck et al. ( 2018 ) mention that there is a spectrum from fake to satirical news that they found to be exploited by many fake news sites. These sites used disclaimers at the bottom of their webpages to suggest they were “satirical” even when there was nothing satirical about their articles, to protect them from accusations about being fake. The difference with a satirical form of fake news is that the authors or the host present themselves as a comedian or as an entertainer rather than a journalist informing the public (Collins et al. 2020 ). However, most audiences believed the information passed in this satirical form because the comedian usually projects news from mainstream media and frames them to suit their program (Collins et al. 2020 ).

Propaganda refers to news stories created by political entities to mislead people. It is a special instance of fabricated stories that aim to harm the interests of a particular party and, typically, has a political context (Zannettou et al. 2019 ). Propaganda was widely used during both World Wars (Collins et al. 2020 ) and during the Cold War (Zannettou et al. 2019 ). It is a consequential type of false information as it can change the course of human history (e.g., by changing the outcome of an election) (Zannettou et al. 2019 ). States are the main actors of propaganda. Recently, propaganda has been used by politicians and media organizations to support a certain position or view (Collins et al. 2020 ). Online astroturfing can be an example of the tools used for the dissemination of propaganda. It is a covert manipulation of public opinion (Peng et al. 2017 ) that aims to make it seem that many people share the same opinion about something. Astroturfing can affect different domains of interest, based on which online astroturfing can be mainly divided into political astroturfing, corporate astroturfing and astroturfing in e-commerce or online services (Mahbub et al. 2019 ). Propaganda types of fake news can be debunked with manual fact-based detection models such as the use of expert-based fact-checkers (Collins et al. 2020 ).

Framing refers to employing some aspect of reality to make content more visible, while the truth is concealed (Collins et al. 2020 ) to deceive and misguide readers. People will understand certain concepts based on the way they are coined and invented. An example of framing was provided by Collins et al. ( 2020 ): “suppose a leader X says “I will neutralize my opponent” simply meaning he will beat his opponent in a given election. Such a statement will be framed such as “leader X threatens to kill Y” and this framed statement provides a total misrepresentation of the original meaning.

Conspiracy Theories

Conspiracy theories refer to the belief that an event is the result of secret plots generated by powerful conspirators. Conspiracy belief refers to people’s adoption and belief of conspiracy theories, and it is associated with psychological, political and social factors (Douglas et al. 2019 ). Conspiracy theories are widespread in contemporary democracies (Sutton and Douglas 2020 ), and they have major consequences. For instance, lately and during the COVID-19 pandemic, conspiracy theories have been discussed from a public health perspective (Meese et al. 2020 ; Allington et al. 2020 ; Freeman et al. 2020 ).

Comparison Between Most Popular Intent-based Types of Fake News

Following a review of the most popular intent-based types of fake news, we compare them as shown in Table  5 based on the most common criteria mentioned by researchers in their definitions as listed below.

• the intent behind the news, which refers to whether a given news type was mainly created to intentionally deceive people or not (e.g., humor, irony, entertainment, etc.);
• the way that the news propagates through OSN, which determines the nature of the propagation of each type of fake news and this can be either fast or slow propagation;
• the severity of the impact of the news on OSN users, which refers to whether the public has been highly impacted by the given type of fake news; the mentioned impact of each fake news type is mainly the proportion of the negative impact;
• and the goal behind disseminating the news, which can be to gain popularity for a particular entity (e.g., political party), for profit (e.g., lucrative business), or other reasons such as humor and irony in the case of satire, spreading panic or anger, and manipulating the public in the case of hoaxes, made-up stories about a particular person or entity in the case of rumors, and misguiding readers in the case of framing.

However, the comparison provided in Table  5 is deduced from the studied research papers; it is our point of view, which is not based on empirical data.

We suspect that the most dangerous types of fake news are the ones with high intention to deceive the public, fast propagation through social media, high negative impact on OSN users, and complicated hidden goals and agendas. However, while the other types of fake news are less dangerous, they should not be ignored.

Moreover, it is important to highlight that the existence of the overlap in the types of fake news mentioned above has been proven, thus it is possible to observe false information that may fall within multiple categories (Zannettou et al. 2019 ). Here, we provide two examples by Zannettou et al. ( 2019 ) to better understand possible overlaps: (1) a rumor may also use clickbait techniques to increase the audience that will read the story; and (2) propaganda stories, as a special instance of a framing story.

Challenges related to fake news detection and mitigation

To alleviate fake news and its threats, it is crucial to first identify and understand the factors involved that continue to challenge researchers. Thus, the main question is to explore and investigate the factors that make it easier to fall for manipulated information. Despite the tremendous progress made in alleviating some of the challenges in fake news detection (Sharma et al. 2019 ; Zhou and Zafarani 2020 ; Zhang and Ghorbani 2020 ; Shu et al. 2020a ), much more work needs to be accomplished to address the problem effectively.

In this section, we discuss several open issues that have been making fake news detection in social media a challenging problem. These issues can be summarized as follows: content-based issues (i.e., deceptive content that resembles the truth very closely), contextual issues (i.e., lack of user awareness, social bots spreaders of fake content, and OSN’s dynamic natures that leads to the fast propagation), as well as the issue of existing datasets (i.e., there still no one size fits all benchmark dataset for fake news detection). These various aspects have proven (Shu et al. 2017 ) to have a great impact on the accuracy of fake news detection approaches.

Content-based issue, deceptive content

Automatic fake news detection remains a huge challenge, primarily because the content is designed in a way that it closely resembles the truth. Besides, most deceivers choose their words carefully and use their language strategically to avoid being caught. Therefore, it is often hard to determine its veracity by AI without the reliance on additional information from third parties such as fact-checkers.

Abdullah-All-Tanvir et al. ( 2020 ) reported that fake news tends to have more complicated stories and hardly ever make any references. It is more likely to contain a greater number of words that express negative emotions. This makes it so complicated that it becomes impossible for a human to manually detect the credibility of this content. Therefore, detecting fake news on social media is quite challenging. Moreover, fake news appears in multiple types and forms, which makes it hard and challenging to define a single global solution able to capture and deal with the disseminated content. Consequently, detecting false information is not a straightforward task due to its various types and forms Zannettou et al. ( 2019 ).

Contextual issues

Contextual issues are challenges that we suspect may not be related to the content of the news but rather they are inferred from the context of the online news post (i.e., humans are the weakest factor due to lack of user awareness, social bots spreaders, dynamic nature of online social platforms and fast propagation of fake news).

Humans are the weakest factor due to the lack of awareness

Recent statistics 31 show that the percentage of unintentional fake news spreaders (people who share fake news without the intention to mislead) over social media is five times higher than intentional spreaders. Moreover, another recent statistic 32 shows that the percentage of people who were confident about their ability to discern fact from fiction is ten times higher than those who were not confident about the truthfulness of what they are sharing. As a result, we can deduce the lack of human awareness about the ascent of fake news.

Public susceptibility and lack of user awareness (Sharma et al. 2019 ) have always been the most challenging problem when dealing with fake news and misinformation. This is a complex issue because many people believe almost everything on the Internet and the ones who are new to digital technology or have less expertise may be easily fooled (Edgerly et al. 2020 ).

Moreover, it has been widely proven (Metzger et al. 2020 ; Edgerly et al. 2020 ) that people are often motivated to support and accept information that goes with their preexisting viewpoints and beliefs, and reject information that does not fit in as well. Hence, Shu et al. ( 2017 ) illustrate an interesting correlation between fake news spread and psychological and cognitive theories. They further suggest that humans are more likely to believe information that confirms their existing views and ideological beliefs. Consequently, they deduce that humans are naturally not very good at differentiating real information from fake information.

Recent research by Giachanou et al. ( 2020 ) studies the role of personality and linguistic patterns in discriminating between fake news spreaders and fact-checkers. They classify a user as a potential fact-checker or a potential fake news spreader based on features that represent users’ personality traits and linguistic patterns used in their tweets. They show that leveraging personality traits and linguistic patterns can improve the performance in differentiating between checkers and spreaders.

Furthermore, several researchers studied the prevalence of fake news on social networks during (Allcott and Gentzkow 2017 ; Grinberg et al. 2019 ; Guess et al. 2019 ; Baptista and Gradim 2020 ) and after (Garrett and Bond 2021 ) the 2016 US presidential election and found that individuals most likely to engage with fake news sources were generally conservative-leaning, older, and highly engaged with political news.

Metzger et al. ( 2020 ) examine how individuals evaluate the credibility of biased news sources and stories. They investigate the role of both cognitive dissonance and credibility perceptions in selective exposure to attitude-consistent news information. They found that online news consumers tend to perceive attitude-consistent news stories as more accurate and more credible than attitude-inconsistent stories.

Similarly, Edgerly et al. ( 2020 ) explore the impact of news headlines on the audience’s intent to verify whether given news is true or false. They concluded that participants exhibit higher intent to verify the news only when they believe the headline to be true, which is predicted by perceived congruence with preexisting ideological tendencies.

Luo et al. ( 2022 ) evaluate the effects of endorsement cues in social media on message credibility and detection accuracy. Results showed that headlines associated with a high number of likes increased credibility, thereby enhancing detection accuracy for real news but undermining accuracy for fake news. Consequently, they highlight the urgency of empowering individuals to assess both news veracity and endorsement cues appropriately on social media.

Moreover, misinformed people are a greater problem than uninformed people (Kuklinski et al. 2000 ), because the former hold inaccurate opinions (which may concern politics, climate change, medicine) that are harder to correct. Indeed, people find it difficult to update their misinformation-based beliefs even after they have been proved to be false (Flynn et al. 2017 ). Moreover, even if a person has accepted the corrected information, his/her belief may still affect their opinion (Nyhan and Reifler 2015 ).

Falling for disinformation may also be explained by a lack of critical thinking and of the need for evidence that supports information (Vilmer et al. 2018 ; Badawy et al. 2019 ). However, it is also possible that people choose misinformation because they engage in directionally motivated reasoning (Badawy et al. 2019 ; Flynn et al. 2017 ). Online clients are normally vulnerable and will, in general, perceive web-based networking media as reliable, as reported by Abdullah-All-Tanvir et al. ( 2019 ), who propose to mechanize fake news recognition.

It is worth noting that in addition to bots causing the outpouring of the majority of the misrepresentations, specific individuals are also contributing a large share of this issue (Abdullah-All-Tanvir et al. 2019 ). Furthermore, Vosoughi et al. (Vosoughi et al. 2018 ) found that contrary to conventional wisdom, robots have accelerated the spread of real and fake news at the same rate, implying that fake news spreads more than the truth because humans, not robots, are more likely to spread it.

In this case, verified users and those with numerous followers were not necessarily responsible for spreading misinformation of the corrupted posts (Abdullah-All-Tanvir et al. 2019 ).

Viral fake news can cause much havoc to our society. Therefore, to mitigate the negative impact of fake news, it is important to analyze the factors that lead people to fall for misinformation and to further understand why people spread fake news (Cheng et al. 2020 ). Measuring the accuracy, credibility, veracity and validity of news contents can also be a key countermeasure to consider.

Social bots spreaders

Several authors (Shu et al. 2018b , 2017 ; Shi et al. 2019 ; Bessi and Ferrara 2016 ; Shao et al. 2018a ) have also shown that fake news is likely to be created and spread by non-human accounts with similar attributes and structure in the network, such as social bots (Ferrara et al. 2016 ). Bots (short for software robots) exist since the early days of computers. A social bot is a computer algorithm that automatically produces content and interacts with humans on social media, trying to emulate and possibly alter their behavior (Ferrara et al. 2016 ). Although they are designed to provide a useful service, they can be harmful, for example when they contribute to the spread of unverified information or rumors (Ferrara et al. 2016 ). However, it is important to note that bots are simply tools created and maintained by humans for some specific hidden agendas.

Social bots tend to connect with legitimate users instead of other bots. They try to act like a human with fewer words and fewer followers on social media. This contributes to the forwarding of fake news (Jiang et al. 2019 ). Moreover, there is a difference between bot-generated and human-written clickbait (Le et al. 2019 ).

Many researchers have addressed ways of identifying and analyzing possible sources of fake news spread in social media. Recent research by Shu et al. ( 2020a ) describes social bots use of two strategies to spread low-credibility content. First, they amplify interactions with content as soon as it is created to make it look legitimate and to facilitate its spread across social networks. Next, they try to increase public exposure to the created content and thus boost its perceived credibility by targeting influential users that are more likely to believe disinformation in the hope of getting them to “repost” the fabricated content. They further discuss the social bot detection systems taxonomy proposed by Ferrara et al. ( 2016 ) which divides bot detection methods into three classes: (1) graph-based, (2) crowdsourcing and (3) feature-based social bot detection methods.

Similarly, Shao et al. ( 2018a ) examine social bots and how they promote the spread of misinformation through millions of Twitter posts during and following the 2016 US presidential campaign. They found that social bots played a disproportionate role in spreading articles from low-credibility sources by amplifying such content in the early spreading moments and targeting users with many followers through replies and mentions to expose them to this content and induce them to share it.

Ismailov et al. ( 2020 ) assert that the techniques used to detect bots depend on the social platform and the objective. They note that a malicious bot designed to make friends with as many accounts as possible will require a different detection approach than a bot designed to repeatedly post links to malicious websites. Therefore, they identify two models for detecting malicious accounts, each using a different set of features. Social context models achieve detection by examining features related to an account’s social presence including features such as relationships to other accounts, similarities to other users’ behaviors, and a variety of graph-based features. User behavior models primarily focus on features related to an individual user’s behavior, such as frequency of activities (e.g., number of tweets or posts per time interval), patterns of activity and clickstream sequences.

Therefore, it is crucial to consider bot detection techniques to distinguish bots from normal users to better leverage user profile features to detect fake news.

However, there is also another “bot-like” strategy that aims to massively promote disinformation and fake content in social platforms, which is called bot farms or also troll farms. It is not social bots, but it is a group of organized individuals engaging in trolling or bot-like promotion of narratives in a coordinated fashion (Wardle 2018 ) hired to massively spread fake news or any other harmful content. A prominent troll farm example is the Russia-based Internet Research Agency (IRA), which disseminated inflammatory content online to influence the outcome of the 2016 U.S. presidential election. 33 As a result, Twitter suspended accounts connected to the IRA and deleted 200,000 tweets from Russian trolls (Jamieson 2020 ). Another example to mention in this category is review bombing (Moro and Birt 2022 ). Review bombing refers to coordinated groups of people massively performing the same negative actions online (e.g., dislike, negative review/comment) on an online video, game, post, product, etc., in order to reduce its aggregate review score. The review bombers can be both humans and bots coordinated in order to cause harm and mislead people by falsifying facts.

Dynamic nature of online social platforms and fast propagation of fake news

Sharma et al. ( 2019 ) affirm that the fast proliferation of fake news through social networks makes it hard and challenging to assess the information’s credibility on social media. Similarly, Qian et al. ( 2018 ) assert that fake news and fabricated content propagate exponentially at the early stage of its creation and can cause a significant loss in a short amount of time (Friggeri et al. 2014 ) including manipulating the outcome of political events (Liu and Wu 2018 ; Bessi and Ferrara 2016 ).

Moreover, while analyzing the way source and promoters of fake news operate over the web through multiple online platforms, Zannettou et al. ( 2019 ) discovered that false information is more likely to spread across platforms (18% appearing on multiple platforms) compared to real information (11%).

Furthermore, recently, Shu et al. ( 2020c ) attempted to understand the propagation of disinformation and fake news in social media and found that such content is produced and disseminated faster and easier through social media because of the low barriers that prevent doing so. Similarly, Shu et al. ( 2020b ) studied hierarchical propagation networks for fake news detection. They performed a comparative analysis between fake and real news from structural, temporal and linguistic perspectives. They demonstrated the potential of using these features to detect fake news and they showed their effectiveness for fake news detection as well.

Lastly, Abdullah-All-Tanvir et al. ( 2020 ) note that it is almost impossible to manually detect the sources and authenticity of fake news effectively and efficiently, due to its fast circulation in such a small amount of time. Therefore, it is crucial to note that the dynamic nature of the various online social platforms, which results in the continued rapid and exponential propagation of such fake content, remains a major challenge that requires further investigation while defining innovative solutions for fake news detection.

Datasets issue

The existing approaches lack an inclusive dataset with derived multidimensional information to detect fake news characteristics to achieve higher accuracy of machine learning classification model performance (Nyow and Chua 2019 ). These datasets are primarily dedicated to validating the machine learning model and are the ultimate frame of reference to train the model and analyze its performance. Therefore, if a researcher evaluates their model based on an unrepresentative dataset, the validity and the efficiency of the model become questionable when it comes to applying the fake news detection approach in a real-world scenario.

Moreover, several researchers (Shu et al. 2020d ; Wang et al. 2020 ; Pathak and Srihari 2019 ; Przybyla 2020 ) believe that fake news is diverse and dynamic in terms of content, topics, publishing methods and media platforms, and sophisticated linguistic styles geared to emulate true news. Consequently, training machine learning models on such sophisticated content requires large-scale annotated fake news data that are difficult to obtain (Shu et al. 2020d ).

Therefore, datasets are also a great topic to work on to enhance data quality and have better results while defining our solutions. Adversarial learning techniques (e.g., GAN, SeqGAN) can be used to provide machine-generated data that can be used to train deeper models and build robust systems to detect fake examples from the real ones. This approach can be used to counter the lack of datasets and the scarcity of data available to train models.

Fake news detection literature review

Fake news detection in social networks is still in the early stage of development and there are still challenging issues that need further investigation. This has become an emerging research area that is attracting huge attention.

There are various research studies on fake news detection in online social networks. Few of them have focused on the automatic detection of fake news using artificial intelligence techniques. In this section, we review the existing approaches used in automatic fake news detection, as well as the techniques that have been adopted. Then, a critical discussion built on a primary classification scheme based on a specific set of criteria is also emphasized.

Categories of fake news detection

In this section, we give an overview of most of the existing automatic fake news detection solutions adopted in the literature. A recent classification by Sharma et al. ( 2019 ) uses three categories of fake news identification methods. Each category is further divided based on the type of existing methods (i.e., content-based, feedback-based and intervention-based methods). However, a review of the literature for fake news detection in online social networks shows that the existing studies can be classified into broader categories based on two major aspects that most authors inspect and make use of to define an adequate solution. These aspects can be considered as major sources of extracted information used for fake news detection and can be summarized as follows: the content-based (i.e., related to the content of the news post) and the contextual aspect (i.e., related to the context of the news post).

Consequently, the studies we reviewed can be classified into three different categories based on the two aspects mentioned above (the third category is hybrid). As depicted in Fig.  5 , fake news detection solutions can be categorized as news content-based approaches, the social context-based approaches that can be divided into network and user-based approaches, and hybrid approaches. The latter combines both content-based and contextual approaches to define the solution.

Classification of fake news detection approaches

News Content-based Category

News content-based approaches are fake news detection approaches that use content information (i.e., information extracted from the content of the news post) and that focus on studying and exploiting the news content in their proposed solutions. Content refers to the body of the news, including source, headline, text and image-video, which can reflect subtle differences.

Researchers of this category rely on content-based detection cues (i.e., text and multimedia-based cues), which are features extracted from the content of the news post. Text-based cues are features extracted from the text of the news, whereas multimedia-based cues are features extracted from the images and videos attached to the news. Figure  6 summarizes the most widely used news content representation (i.e., text and multimedia/images) and detection techniques (i.e., machine learning (ML), deep Learning (DL), natural language processing (NLP), fact-checking, crowdsourcing (CDS) and blockchain (BKC)) in news content-based category of fake news detection approaches. Most of the reviewed research works based on news content for fake news detection rely on the text-based cues (Kapusta et al. 2019 ; Kaur et al. 2020 ; Vereshchaka et al. 2020 ; Ozbay and Alatas 2020 ; Wang 2017 ; Nyow and Chua 2019 ; Hosseinimotlagh and Papalexakis 2018 ; Abdullah-All-Tanvir et al. 2019 , 2020 ; Mahabub 2020 ; Bahad et al. 2019 ; Hiriyannaiah et al. 2020 ) extracted from the text of the news content including the body of the news and its headline. However, a few researchers such as Vishwakarma et al. ( 2019 ) and Amri et al. ( 2022 ) try to recognize text from the associated image.

News content-based category: news content representation and detection techniques

Most researchers of this category rely on artificial intelligence (AI) techniques (such as ML, DL and NLP models) to improve performance in terms of prediction accuracy. Others use different techniques such as fact-checking, crowdsourcing and blockchain. Specifically, the AI- and ML-based approaches in this category are trying to extract features from the news content, which they use later for content analysis and training tasks. In this particular case, the extracted features are the different types of information considered to be relevant for the analysis. Feature extraction is considered as one of the best techniques to reduce data size in automatic fake news detection. This technique aims to choose a subset of features from the original set to improve classification performance (Yazdi et al. 2020 ).

Table  6 lists the distinct features and metadata, as well as the used datasets in the news content-based category of fake news detection approaches.

The features and datasets used in the news content-based approaches

a https://www.kaggle.com/anthonyc1/gathering-real-news-for-oct-dec-2016 , last access date: 26-12-2022

b https://mediabiasfactcheck.com/ , last access date: 26-12-2022

c https://github.com/KaiDMML/FakeNewsNet , last access date: 26-12-2022

d https://www.kaggle.com/anthonyc1/gathering-real-news-for-oct-dec-2016 , last access date: 26-12-2022

e https://www.cs.ucsb.edu/~william/data/liar_dataset.zip , last access date: 26-12-2022

f https://www.kaggle.com/mrisdal/fake-news , last access date: 26-12-2022

g https://github.com/BuzzFeedNews/2016-10-facebook-fact-check , last access date: 26-12-2022

h https://www.politifact.com/subjects/fake-news/ , last access date: 26-12-2022

i https://www.kaggle.com/rchitic17/real-or-fake , last access date: 26-12-2022

j https://www.kaggle.com/jruvika/fake-news-detection , last access date: 26-12-2022

k https://github.com/MKLab-ITI/image-verification-corpus , last access date: 26-12-2022

l https://drive.google.com/file/d/14VQ7EWPiFeGzxp3XC2DeEHi-BEisDINn/view , last access date: 26-12-2022

Social Context-based Category

Unlike news content-based solutions, the social context-based approaches capture the skeptical social context of the online news (Zhang and Ghorbani 2020 ) rather than focusing on the news content. The social context-based category contains fake news detection approaches that use the contextual aspects (i.e., information related to the context of the news post). These aspects are based on social context and they offer additional information to help detect fake news. They are the surrounding data outside of the fake news article itself, where they can be an essential part of automatic fake news detection. Some useful examples of contextual information may include checking if the news itself and the source that published it are credible, checking the date of the news or the supporting resources, and checking if any other online news platforms are reporting the same or similar stories (Zhang and Ghorbani 2020 ).

Social context-based aspects can be classified into two subcategories, user-based and network-based, and they can be used for context analysis and training tasks in the case of AI- and ML-based approaches. User-based aspects refer to information captured from OSN users such as user profile information (Shu et al. 2019b ; Wang et al. 2019c ; Hamdi et al. 2020 ; Nyow and Chua 2019 ; Jiang et al. 2019 ) and user behavior (Cardaioli et al. 2020 ) such as user engagement (Uppada et al. 2022 ; Jiang et al. 2019 ; Shu et al. 2018b ; Nyow and Chua 2019 ) and response (Zhang et al. 2019a ; Qian et al. 2018 ). Meanwhile, network-based aspects refer to information captured from the properties of the social network where the fake content is shared and disseminated such as news propagation path (Liu and Wu 2018 ; Wu and Liu 2018 ) (e.g., propagation times and temporal characteristics of propagation), diffusion patterns (Shu et al. 2019a ) (e.g., number of retweets, shares), as well as user relationships (Mishra 2020 ; Hamdi et al. 2020 ; Jiang et al. 2019 ) (e.g., friendship status among users).

Figure  7 summarizes some of the most widely adopted social context representations, as well as the most used detection techniques (i.e., AI, ML, DL, fact-checking and blockchain), in the social context-based category of approaches.

Social context-based category: social context representation and detection techniques

Table  7 lists the distinct features and metadata, the adopted detection cues, as well as the used datasets, in the context-based category of fake news detection approaches.

The features, detection cues and datasets used int the social context-based approaches

a https://www.dropbox.com/s/7ewzdrbelpmrnxu/rumdetect2017.zip , last access date: 26-12-2022 b https://snap.stanford.edu/data/ego-Twitter.html , last access date: 26-12-2022

Hybrid approaches

Most researchers are focusing on employing a specific method rather than a combination of both content- and context-based methods. This is because some of them (Wu and Rao 2020 ) believe that there still some challenging limitations in the traditional fusion strategies due to existing feature correlations and semantic conflicts. For this reason, some researchers focus on extracting content-based information, while others are capturing some social context-based information for their proposed approaches.

However, it has proven challenging to successfully automate fake news detection based on just a single type of feature (Ruchansky et al. 2017 ). Therefore, recent directions tend to do a mixture by using both news content-based and social context-based approaches for fake news detection.

Table  8 lists the distinct features and metadata, as well as the used datasets, in the hybrid category of fake news detection approaches.

The features and datasets used in the hybrid approaches

Fake news detection techniques

Another vision for classifying automatic fake news detection is to look at techniques used in the literature. Hence, we classify the detection methods based on the techniques into three groups:

• Human-based techniques: This category mainly includes the use of crowdsourcing and fact-checking techniques, which rely on human knowledge to check and validate the veracity of news content.
• Artificial Intelligence-based techniques: This category includes the most used AI approaches for fake news detection in the literature. Specifically, these are the approaches in which researchers use classical ML, deep learning techniques such as convolutional neural network (CNN), recurrent neural network (RNN), as well as natural language processing (NLP).
• Blockchain-based techniques: This category includes solutions using blockchain technology to detect and mitigate fake news in social media by checking source reliability and establishing the traceability of the news content.

Human-based Techniques

One specific research direction for fake news detection consists of using human-based techniques such as crowdsourcing (Pennycook and Rand 2019 ; Micallef et al. 2020 ) and fact-checking (Vlachos and Riedel 2014 ; Chung and Kim 2021 ; Nyhan et al. 2020 ) techniques.

These approaches can be considered as low computational requirement techniques since both rely on human knowledge and expertise for fake news detection. However, fake news identification cannot be addressed solely through human force since it demands a lot of effort in terms of time and cost, and it is ineffective in terms of preventing the fast spread of fake content.

Crowdsourcing. Crowdsourcing approaches (Kim et al. 2018 ) are based on the “wisdom of the crowds” (Collins et al. 2020 ) for fake content detection. These approaches rely on the collective contributions and crowd signals (Tschiatschek et al. 2018 ) of a group of people for the aggregation of crowd intelligence to detect fake news (Tchakounté et al. 2020 ) and to reduce the spread of misinformation on social media (Pennycook and Rand 2019 ; Micallef et al. 2020 ).

Micallef et al. ( 2020 ) highlight the role of the crowd in countering misinformation. They suspect that concerned citizens (i.e., the crowd), who use platforms where disinformation appears, can play a crucial role in spreading fact-checking information and in combating the spread of misinformation.

Recently Tchakounté et al. ( 2020 ) proposed a voting system as a new method of binary aggregation of opinions of the crowd and the knowledge of a third-party expert. The aggregator is based on majority voting on the crowd side and weighted averaging on the third-party site.

Similarly, Huffaker et al. ( 2020 ) propose a crowdsourced detection of emotionally manipulative language. They introduce an approach that transforms classification problems into a comparison task to mitigate conflation content by allowing the crowd to detect text that uses manipulative emotional language to sway users toward positions or actions. The proposed system leverages anchor comparison to distinguish between intrinsically emotional content and emotionally manipulative language.

La Barbera et al. ( 2020 ) try to understand how people perceive the truthfulness of information presented to them. They collect data from US-based crowd workers, build a dataset of crowdsourced truthfulness judgments for political statements, and compare it with expert annotation data generated by fact-checkers such as PolitiFact.

Coscia and Rossi ( 2020 ) introduce a crowdsourced flagging system that consists of online news flagging. The bipolar model of news flagging attempts to capture the main ingredients that they observe in empirical research on fake news and disinformation.

Unlike the previously mentioned researchers who focus on news content in their approaches, Pennycook and Rand ( 2019 ) focus on using crowdsourced judgments of the quality of news sources to combat social media disinformation.

Fact-Checking. The fact-checking task is commonly manually performed by journalists to verify the truthfulness of a given claim. Indeed, fact-checking features are being adopted by multiple online social network platforms. For instance, Facebook 34 started addressing false information through independent fact-checkers in 2017, followed by Google 35 the same year. Two years later, Instagram 36 followed suit. However, the usefulness of fact-checking initiatives is questioned by journalists 37 , as well as by researchers such as Andersen and Søe ( 2020 ). On the other hand, work is being conducted to boost the effectiveness of these initiatives to reduce misinformation (Chung and Kim 2021 ; Clayton et al. 2020 ; Nyhan et al. 2020 ).

Most researchers use fact-checking websites (e.g., politifact.com, 38 snopes.com, 39 Reuters, 40 , etc.) as data sources to build their datasets and train their models. Therefore, in the following, we specifically review examples of solutions that use fact-checking (Vlachos and Riedel 2014 ) to help build datasets that can be further used in the automatic detection of fake content.

Yang et al. ( 2019a ) use PolitiFact fact-checking website as a data source to train, tune, and evaluate their model named XFake, on political data. The XFake system is an explainable fake news detector that assists end users to identify news credibility. The fakeness of news items is detected and interpreted considering both content and contextual (e.g., statements) information (e.g., speaker).

Based on the idea that fact-checkers cannot clean all data, and it must be a selection of what “matters the most” to clean while checking a claim, Sintos et al. ( 2019 ) propose a solution to help fact-checkers combat problems related to data quality (where inaccurate data lead to incorrect conclusions) and data phishing. The proposed solution is a combination of data cleaning and perturbation analysis to avoid uncertainties and errors in data and the possibility that data can be phished.

Tchechmedjiev et al. ( 2019 ) propose a system named “ClaimsKG” as a knowledge graph of fact-checked claims aiming to facilitate structured queries about their truth values, authors, dates, journalistic reviews and other kinds of metadata. “ClaimsKG” designs the relationship between vocabularies. To gather vocabularies, a semi-automated pipeline periodically gathers data from popular fact-checking websites regularly.

AI-based Techniques

Previous work by Yaqub et al. ( 2020 ) has shown that people lack trust in automated solutions for fake news detection However, work is already being undertaken to increase this trust, for instance by von der Weth et al. ( 2020 ).

Most researchers consider fake news detection as a classification problem and use artificial intelligence techniques, as shown in Fig.  8 . The adopted AI techniques may include machine learning ML (e.g., Naïve Bayes, logistic regression, support vector machine SVM), deep learning DL (e.g., convolutional neural networks CNN, recurrent neural networks RNN, long short-term memory LSTM) and natural language processing NLP (e.g., Count vectorizer, TF-IDF Vectorizer). Most of them combine many AI techniques in their solutions rather than relying on one specific approach.

Examples of the most widely used AI techniques for fake news detection

Many researchers are developing machine learning models in their solutions for fake news detection. Recently, deep neural network techniques are also being employed as they are generating promising results (Islam et al. 2020 ). A neural network is a massively parallel distributed processor with simple units that can store important information and make it available for use (Hiriyannaiah et al. 2020 ). Moreover, it has been proven (Cardoso Durier da Silva et al. 2019 ) that the most widely used method for automatic detection of fake news is not simply a classical machine learning technique, but rather a fusion of classical techniques coordinated by a neural network.

Some researchers define purely machine learning models (Del Vicario et al. 2019 ; Elhadad et al. 2019 ; Aswani et al. 2017 ; Hakak et al. 2021 ; Singh et al. 2021 ) in their fake news detection approaches. The more commonly used machine learning algorithms (Abdullah-All-Tanvir et al. 2019 ) for classification problems are Naïve Bayes, logistic regression and SVM.

Other researchers (Wang et al. 2019c ; Wang 2017 ; Liu and Wu 2018 ; Mishra 2020 ; Qian et al. 2018 ; Zhang et al. 2020 ; Goldani et al. 2021 ) prefer to do a mixture of different deep learning models, without combining them with classical machine learning techniques. Some even prove that deep learning techniques outperform traditional machine learning techniques (Mishra et al. 2022 ). Deep learning is one of the most widely popular research topics in machine learning. Unlike traditional machine learning approaches, which are based on manually crafted features, deep learning approaches can learn hidden representations from simpler inputs both in context and content variations (Bondielli and Marcelloni 2019 ). Moreover, traditional machine learning algorithms almost always require structured data and are designed to “learn” to act by understanding labeled data and then use it to produce new results with more datasets, which requires human intervention to “teach them” when the result is incorrect (Parrish 2018 ), while deep learning networks rely on layers of artificial neural networks (ANN) and do not require human intervention, as multilevel layers in neural networks place data in a hierarchy of different concepts, which ultimately learn from their own mistakes (Parrish 2018 ). The two most widely implemented paradigms in deep neural networks are recurrent neural networks (RNN) and convolutional neural networks (CNN).

Still other researchers (Abdullah-All-Tanvir et al. 2019 ; Kaliyar et al. 2020 ; Zhang et al. 2019a ; Deepak and Chitturi 2020 ; Shu et al. 2018a ; Wang et al. 2019c ) prefer to combine traditional machine learning and deep learning classification, models. Others combine machine learning and natural language processing techniques. A few combine deep learning models with natural language processing (Vereshchaka et al. 2020 ). Some other researchers (Kapusta et al. 2019 ; Ozbay and Alatas 2020 ; Ahmed et al. 2020 ) combine natural language processing with machine learning models. Furthermore, others (Abdullah-All-Tanvir et al. 2019 ; Kaur et al. 2020 ; Kaliyar 2018 ; Abdullah-All-Tanvir et al. 2020 ; Bahad et al. 2019 ) prefer to combine all the previously mentioned techniques (i.e., ML, DL and NLP) in their approaches.

Table  11 , which is relegated to the Appendix (after the bibliography) because of its size, shows a comparison of the fake news detection solutions that we have reviewed based on their main approaches, the methodology that was used and the models.

Comparison of AI-based fake news detection techniques

Blockchain-based Techniques for Source Reliability and Traceability

Another research direction for detecting and mitigating fake news in social media focuses on using blockchain solutions. Blockchain technology is recently attracting researchers’ attention due to the interesting features it offers. Immutability, decentralization, tamperproof, consensus, record keeping and non-repudiation of transactions are some of the key features that make blockchain technology exploitable, not just for cryptocurrencies, but also to prove the authenticity and integrity of digital assets.

However, the proposed blockchain approaches are few in number and they are fundamental and theoretical approaches. Specifically, the solutions that are currently available are still in research, prototype, and beta testing stages (DiCicco and Agarwal 2020 ; Tchechmedjiev et al. 2019 ). Furthermore, most researchers (Ochoa et al. 2019 ; Song et al. 2019 ; Shang et al. 2018 ; Qayyum et al. 2019 ; Jing and Murugesan 2018 ; Buccafurri et al. 2017 ; Chen et al. 2018 ) do not specify which fake news type they are mitigating in their studies. They mention news content in general, which is not adequate for innovative solutions. For that, serious implementations should be provided to prove the usefulness and feasibility of this newly developing research vision.

Table  9 shows a classification of the reviewed blockchain-based approaches. In the classification, we listed the following:

• The type of fake news that authors are trying to mitigate, which can be multimedia-based or text-based fake news.
• The techniques used for fake news mitigation, which can be either blockchain only, or blockchain combined with other techniques such as AI, Data mining, Truth-discovery, Preservation metadata, Semantic similarity, Crowdsourcing, Graph theory and SIR model (Susceptible, Infected, Recovered).
• The feature that is offered as an advantage of the given solution (e.g., Reliability, Authenticity and Traceability). Reliability is the credibility and truthfulness of the news content, which consists of proving the trustworthiness of the content. Traceability aims to trace and archive the contents. Authenticity consists of checking whether the content is real and authentic.

A checkmark ( ✓ ) in Table  9 denotes that the mentioned criterion is explicitly mentioned in the proposed solution, while the empty dash (–) cell for fake news type denotes that it depends on the case: The criterion was either not explicitly mentioned (e.g., fake news type) in the work or the classification does not apply (e.g., techniques/other).

A classification of popular blockchain-based approaches for fake news detection in social media

After reviewing the most relevant state of the art for automatic fake news detection, we classify them as shown in Table  10 based on the detection aspects (i.e., content-based, contextual, or hybrid aspects) and the techniques used (i.e., AI, crowdsourcing, fact-checking, blockchain or hybrid techniques). Hybrid techniques refer to solutions that simultaneously combine different techniques from previously mentioned categories (i.e., inter-hybrid methods), as well as techniques within the same class of methods (i.e., intra-hybrid methods), in order to define innovative solutions for fake news detection. A hybrid method should bring the best of both worlds. Then, we provide a discussion based on different axes.

Fake news detection approaches classification

News content-based methods

Most of the news content-based approaches consider fake news detection as a classification problem and they use AI techniques such as classical machine learning (e.g., regression, Bayesian) as well as deep learning (i.e., neural methods such as CNN and RNN). More specifically, classification of social media content is a fundamental task for social media mining, so that most existing methods regard it as a text categorization problem and mainly focus on using content features, such as words and hashtags (Wu and Liu 2018 ). The main challenge facing these approaches is how to extract features in a way to reduce the data used to train their models and what features are the most suitable for accurate results.

Researchers using such approaches are motivated by the fact that the news content is the main entity in the deception process, and it is a straightforward factor to analyze and use while looking for predictive clues of deception. However, detecting fake news only from the content of the news is not enough because the news is created in a strategic intentional way to mimic the truth (i.e., the content can be intentionally manipulated by the spreader to make it look like real news). Therefore, it is considered to be challenging, if not impossible, to identify useful features (Wu and Liu 2018 ) and consequently tell the nature of such news solely from the content.

Moreover, works that utilize only the news content for fake news detection ignore the rich information and latent user intelligence (Qian et al. 2018 ) stored in user responses toward previously disseminated articles. Therefore, the auxiliary information is deemed crucial for an effective fake news detection approach.

Social context-based methods

The context-based approaches explore the surrounding data outside of the news content, which can be an effective direction and has some advantages in areas where the content approaches based on text classification can run into issues. However, most existing studies implementing contextual methods mainly focus on additional information coming from users and network diffusion patterns. Moreover, from a technical perspective, they are limited to the use of sophisticated machine learning techniques for feature extraction, and they ignore the usefulness of results coming from techniques such as web search and crowdsourcing which may save much time and help in the early detection and identification of fake content.

Hybrid approaches can simultaneously model different aspects of fake news such as the content-based aspects, as well as the contextual aspect based on both the OSN user and the OSN network patterns. However, these approaches are deemed more complex in terms of models (Bondielli and Marcelloni 2019 ), data availability, and the number of features. Furthermore, it remains difficult to decide which information among each category (i.e., content-based and context-based information) is most suitable and appropriate to be used to achieve accurate and precise results. Therefore, there are still very few studies belonging to this category of hybrid approaches.

Early detection

As fake news usually evolves and spreads very fast on social media, it is critical and urgent to consider early detection directions. Yet, this is a challenging task to do especially in highly dynamic platforms such as social networks. Both news content- and social context-based approaches suffer from this challenging early detection of fake news.

Although approaches that detect fake news based on content analysis face this issue less, they are still limited by the lack of information required for verification when the news is in its early stage of spread. However, approaches that detect fake news based on contextual analysis are most likely to suffer from the lack of early detection since most of them rely on information that is mostly available after the spread of fake content such as social engagement, user response, and propagation patterns. Therefore, it is crucial to consider both trusted human verification and historical data as an attempt to detect fake content during its early stage of propagation.

Conclusion and future directions

In this paper, we introduced the general context of the fake news problem as one of the major issues of the online deception problem in online social networks. Based on reviewing the most relevant state of the art, we summarized and classified existing definitions of fake news, as well as its related terms. We also listed various typologies and existing categorizations of fake news such as intent-based fake news including clickbait, hoax, rumor, satire, propaganda, conspiracy theories, framing as well as content-based fake news including text and multimedia-based fake news, and in the latter, we can tackle deepfake videos and GAN-generated fake images. We discussed the major challenges related to fake news detection and mitigation in social media including the deceptiveness nature of the fabricated content, the lack of human awareness in the field of fake news, the non-human spreaders issue (e.g., social bots), the dynamicity of such online platforms, which results in a fast propagation of fake content and the quality of existing datasets, which still limits the efficiency of the proposed solutions. We reviewed existing researchers’ visions regarding the automatic detection of fake news based on the adopted approaches (i.e., news content-based approaches, social context-based approaches, or hybrid approaches) and the techniques that are used (i.e., artificial intelligence-based methods; crowdsourcing, fact-checking, and blockchain-based methods; and hybrid methods), then we showed a comparative study between the reviewed works. We also provided a critical discussion of the reviewed approaches based on different axes such as the adopted aspect for fake news detection (i.e., content-based, contextual, and hybrid aspects) and the early detection perspective.

To conclude, we present the main issues for combating the fake news problem that needs to be further investigated while proposing new detection approaches. We believe that to define an efficient fake news detection approach, we need to consider the following:

• Our choice of sources of information and search criteria may have introduced biases in our research. If so, it would be desirable to identify those biases and mitigate them.
• News content is the fundamental source to find clues to distinguish fake from real content. However, contextual information derived from social media users and from the network can provide useful auxiliary information to increase detection accuracy. Specifically, capturing users’ characteristics and users’ behavior toward shared content can be a key task for fake news detection.
• Moreover, capturing users’ historical behavior, including their emotions and/or opinions toward news content, can help in the early detection and mitigation of fake news.
• Furthermore, adversarial learning techniques (e.g., GAN, SeqGAN) can be considered as a promising direction for mitigating the lack and scarcity of available datasets by providing machine-generated data that can be used to train and build robust systems to detect the fake examples from the real ones.
• Lastly, analyzing how sources and promoters of fake news operate over the web through multiple online platforms is crucial; Zannettou et al. ( 2019 ) discovered that false information is more likely to spread across platforms (18% appearing on multiple platforms) compared to valid information (11%).

Appendix: A Comparison of AI-based fake news detection techniques

This Appendix consists only in the rather long Table  11 . It shows a comparison of the fake news detection solutions based on artificial intelligence that we have reviewed according to their main approaches, the methodology that was used, and the models, as explained in Sect.  6.2.2 .

Author Contributions

The order of authors is alphabetic as is customary in the third author’s field. The lead author was Sabrine Amri, who collected and analyzed the data and wrote a first draft of the paper, all along under the supervision and tight guidance of Esma Aïmeur. Gilles Brassard reviewed, criticized and polished the work into its final form.

This work is supported in part by Canada’s Natural Sciences and Engineering Research Council.

Availability of data and material

Declarations.

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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A Comprehensive Dive Into Social Media Marketing Case Studies

Nowadays, social media goes far beyond chatting with friends on Facebook. Where we’re all connected online, it’s more than just a way to keep in touch with friends. Business owners all over the world are finding it to be an extremely useful tool.

Think about how social media has changed over the years. In the beginning, it was all about talking to your buddies online.

But as time passed, it became a big deal for companies too. Now, it’s a key part of integrated marketing campaigns for all sorts of businesses, no matter how big or small. It helps them connect with the people who might want to buy their stuff.

Social media marketing has grown into something really important for people who want to sell stuff. It’s a cool way to talk to potential customers and get them interested in what you’re selling.

To prove how powerful social media can be, we’ve put together some awesome social media case studies about how it has changed everything.

So, let’s know more about it!

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The significance of social media case studies.

Before we delve into the specifics of these social media case studies, it is imperative to underscore the vital role they play in the realm of digital marketing.

A Social media marketing case study serves as tangible, real-world evidence of successful strategies, offering invaluable insights and actionable takeaways applicable to businesses of all sizes.

Case studies are like beacons in the digital marketing world as they provide a clear path forward by showcasing what has worked for others.

These real-life success stories serve as a source of inspiration and guidance, offering a roadmap for businesses looking to harness the power of social media.

The Influence of Social Proof

As inherently social beings, we often find ourselves seeking assurance from the experiences and achievements of others when making decisions.

In the same way, social media case studies provide a compelling form of social proof, instilling confidence in potential clients by demonstrating the viability of specific strategies.

When consumers see concrete evidence of how a particular social media strategy led to success for a business, it not only validates the effectiveness of that strategy but also builds trust.

This trust is a critical element in the decision-making process for consumers, making them more likely to engage with and ultimately support a brand.

Decoding the Science Behind Successful Social Media Marketing

Airbnb’s spectacular ascent.

In the annals of business history, Airbnb’s meteoric rise from a struggling startup in 2008 to a global hospitality juggernaut is nothing short of remarkable.

This particular case study on social media serves as a quintessential illustration of how Airbnb harnessed the power of user-generated content and tapped into the emotional resonance of travel to create a viral sensation.

Airbnb’s journey is not just a success story; it’s a masterclass in the art of storytelling through social media.

By encouraging users to share their travel experiences through captivating photos and videos, Airbnb not only engaged its audience but also created a sense of community. This sense of community is a potent driver of brand loyalty and advocacy.

The lesson from these social media case studies is clear: storytelling is at the heart of effective social media marketing. It’s not just about promoting products or services; it’s about crafting narratives that resonate with your audience on a personal level.

Navigating Challenges through the Lens of Social Media Marketing

Mcdonald’s “our food, your questions” campaign.

Even titans like McDonald’s, one of the world’s most iconic brands, encounter public skepticism. Facing questions about the quality of their food, McDonald’s responded with the “Our Food, Your Questions” campaign.

This insight, among other social media case studies, delves into how the fast-food giant used transparency and active social media engagement to rebuild trust with consumers.

McDonald’s recognized that addressing consumer concerns head-on was not just a PR move but a strategic decision. By openly addressing questions and concerns about their food, they demonstrated transparency and a commitment to quality.

This level of transparency resonated with consumers, fostering a renewed sense of trust.

Well! In the quest for social media success, having the right tools at your disposal is paramount. Socinator offers a comprehensive solution for automating, managing, and optimizing your social media campaigns. With Socinator, you can!

Let’s know how Socinator can help marketers to create a powerful impact on multiple social media platforms in just a few clicks!

Socinator: Your Social Media Partner

While we’re on the topic of effective social media strategies, it’s essential to mention Socinator—a powerful tool that can enhance your social media marketing efforts.

Socinator is your partner in optimizing and automating social media campaigns across various platforms.

Here is what Socinator offers to its users:

• You can schedule posts to be published automatically on a specific date, so you don’t have to post them yourself, especially when you’re busy.
• Socinator offers automation capabilities for a variety of tasks, including commenting, liking, following, unfollowing, following back, and reposting.
• Additionally, the tool assists you in discovering and extracting hashtags, identifying target audiences, and with the posting of profile pictures.
• With Socinator, you can efficiently handle numerous accounts, remove posts, block followers, send out broadcast messages, and engage in live chats.

Now, let’s continue exploring more insightful social media case studies that showcase the potential of social media marketing.

Small Enterprises, Monumental Successes

Blendjet’s ingenious instagram-first strategy.

BlendJet, a portable blender company, captured the imagination of Instagram users worldwide with their creative and engaging content.

This social media case study highlights the potential for even modest-sized enterprises to flourish in the digital arena when armed with a well-crafted social media strategy.

BlendJet’s success story underscores the importance of understanding your audience and choosing the right platform for your brand. Instagram, with its visually appealing format, was the perfect canvas for BlendJet’s marketing efforts.

This strategy helped them reach a global audience and fostered a vibrant and engaged community of users.

The Metrics of Social Media Triumph

Hubspot’s data-driven odyssey.

HubSpot, a recognized leader in inbound marketing, embarked on their social media journey with data and analytics as their guiding stars.

This particular case study on social media elucidates how HubSpot meticulously employed metrics such as engagement rates, conversion rates, and customer lifetime value to fine-tune and optimize their social media campaigns.

HubSpot’s approach is a testament to the power of data-driven decision-making in social media marketing. In a world flooded with data, it’s crucial for you to know which metrics matter most to your business.

Tracking key performance indicators (KPIs) and analyzing the data can provide invaluable insights into what’s working and what needs improvement.

Also Read 11 Social Media Marketing Ideas for Non-Profit Charity Organization 5 Remarkable Marketing Campaigns for Your Brand Schedule Instagram Posts For Consistent Success

Unveiling Trends and Innovations in Social Media Marketing

Tiktok’s explosive evolution.

TikTok, the trailblazing short-form video platform, took the world by storm with its innovative approach to content creation. In this social media case study, we embark on a journey to understand the meteoric rise of  TikTok and contemplate its profound implications for the future of social media marketing.

TikTok’s success is a testament to the power of embracing emerging trends. In an ever-evolving digital landscape, staying ahead of the curve is essential.

TikTok’s emphasis on short, engaging videos tapped into the changing preferences of a younger audience. Businesses that adapt to new platforms and formats can gain a competitive edge in the market.

Extracting Insights from Social Media Case Studies

Key takeaways to supercharge your social media strategy.

After immersing ourselves in the captivating narratives of these social media case studies, it is essential to distill the key insights that can invigorate and enhance your own social media marketing efforts.

From the art of storytelling to the science of data-driven decisions, these case studies offer an abundance of actionable wisdom.

As we wrap up our exploration of these social media case studies, let’s summarize the key takeaways that can elevate your social media strategy:

• Storytelling Matters: Craft compelling narratives that resonate with your audience.
• Transparency Builds Trust: To foster trust, it is important to address any concerns in an open and transparent manner.
• Platform Fit: Choose the right social media platform for your brand and audience.
• Data-Driven Decisions: Use metrics and analytics to refine your strategies continuously.
•  Embrace Trends: Stay adaptable and explore emerging trends to remain relevant.

Having a strong online presence is crucial for business success in digital world. Social media case studies are like success stories and guides that can inspire and help you navigate the ever-changing world of social media.

As you embark on your own social media journey, remember that these case studies aren’t just tales of success; they’re like maps showing you the strategies to succeed in the exciting and always-changing world of social media marketing.

Social media is a big, ever-changing place. To do well here, it’s not about luck; it’s about making smart choices, being creative, and staying flexible as trends shift. So, get ready for your social media adventure.

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How to Write a Social Media Case Study: A Handy Template for Agencies

When you’re talking to prospective clients during the sales process, they may want to see proof that you can achieve the results you’re promising them. So why not show them an example of your past achievements?

A social media marketing case study that’s full of persuasive data and client quotes is the perfect way to demonstrate the success customers can expect if they enlist your services.

Though it may take some time to produce, a well-put-together case study is worth the effort. In this article, we’ll explain how to create a social media success story, with some key things to include. And to help you get started, we’ll provide you with an example based on one of our own case studies.

Using quintly, you can automate the whole process of social media data collection , and use the data you’ve collected to create compelling marketing reports and case studies. Learn more about how to collect and analyze your clients’ social media data in a single platform.

What is a social media case study?

A social media case study is an in-depth exploration of one of your biggest client success stories. It describes how you helped them solve their problems and reach their goals.

Often, case studies focus on a specific campaign designed to achieve a certain result. Perhaps your clients wanted to improve ROI on social media by 20%. Or, maybe they were struggling to make an impact on Facebook and looking to improve performance on that channel.

The case study should be based on conversations with your clients and include lots of quotes from them throughout. It should also include evidence and data to back up the claims.

You can publish case studies on your company’s website or blog, and share them with leads as part of your sales funnel.

How to write a social media success story

A customer success story must be relatable, persuasive, and interesting enough to make sure that prospective leads will actually read it. Every marketing case study is different and will follow your client’s unique business and story. While there’s no one-size fits-all approach, there are some elements we think are important to include. If you’re not sure where to begin, here’s a few ideas to get you started.

1. Reach out to your client

First, you need to ask the right clients to participate in your case study. Choose a company that came to you with a specific problem or goal, and with your help has been able to overcome challenges and achieve great results.

Ideally, the featured business should be similar to the ideal clients you are hoping to attract , so that potential clients can relate to their problems and desires.

You’ll need to reach out and make sure they’re happy for you to feature them in the case study, and don’t mind investing some of their time. It may take a while for all the decision-makers to agree and sign off on the project, so allow plenty of time for this process. Once you have their agreement, you can start preparing to interview them.

2. Conduct an interview for your case study

The client interview is one of the most important steps because their feedback will become the backbone of the case study. 

You could send your client over a list of questions and ask them to respond by email. However, it’s better to set up a conversation with one or two representatives from the company , either by phone or video call, so you can have a more natural conversation and get deeper insights.

It’s important that you don’t go into a client interview cold. Being prepared means doing your research so that you won’t waste your or your client’s time.

Before the call, send over your questions so that they can start thinking about their answers. You should also request any assets or information you might need for the case study, such as the company logo and images you’ll want to use.

Ask lots of open-ended questions that elicit detailed responses. Try to cover every angle so you won’t have to go back and forth later for further clarification.

Here are a few example questions:

• Why does social media matter for your brand?
• What were your biggest challenges regarding social media marketing?
• How have our services helped you overcome those challenges?
• What’s changed in your social media and marketing strategy since we began working together?

Check that it’s ok to record the call so you can focus on the conversation and not have to worry about taking notes. A transcription software such as Otter.ai (available with a free plan) can help you record audio and transcribe it.

3. Compile data from social media analytics

Along with customer quotes, backing up your good work with social media data will go a long way. 

When it comes to persuading new clients that you’ve got what it takes to help them overcome their challenges and reach their objectives, there’s nothing more convincing than hard data.

It shows that your past campaigns have objectively performed well, and you’re not just interpreting your results as positive. And, it builds trust with prospective customers because it shows that you’re committed to tracking your own progress and keeping yourself accountable. 

Graphs and screenshots also help to make your case study more engaging. You can use them to break up big chunks of text with visuals.

Select the most eye-catching and impressive metrics to include in your case study. If you are using a social media platform such as quintly, you can take screenshots from your dashboards to illustrate the points you’re talking about.

You can include some data comparing your client’s performance with their competitors. 

For example, the graph below shows that even though Barcelona FC and Real Madrid shared roughly the same number of posts on Facebook in the selected period, the Catalan football club had a higher Interaction Rate than its rival:

You can also contrast the client’s current numbers against past results to show the improvement. 

For example, the following graphs show a month-to-month increase in FC Barcelona’s Interaction Rate on Instagram. 

Retrieving high-quality data and presenting it in an easy-to-understand format is essential for creating an effective case study. And, it can shape the way your case study is going to look, depending on what specific data points you decide to focus on. So make sure you have all the necessary metrics and dashboards set up before you begin writing your content. 

4. Write your case study

When you’ve got your client’s responses to your questions and you’ve picked out some key data points to include, it’s time to focus on the content of your case study.

To write an engaging case study, you must first grab the reader’s attention with a great headline that’s brief and clear. It can also mention the company name and a specific result they achieved.

Your headline could be something like: “Company A achieves X% increase in social media conversions with help from Y campaign”.

As a subheading, summarize the contents of the case study in a single sentence so that even those who don’t read the full article will get an idea of what you achieved.

Format your case study as a story with your customer  as the protagonist. This can help to grab the reader’s attention and take them on a journey with you.

When telling the story, remember to: 

• Describe where they began – the problems they were facing and the goals they wanted to achieve.
• Explain what tactics you used to help them, and why you decided on this strategy.
• Talk about how these tactics began to improve their results and bring them closer to hitting their social media KPIs and increasing ROI.
• Keep the focus on your customer , using their own words to describe the situation.

Style and formatting matter . Your case study should be informative yet easy-to-read. So use conversational language and make sure the tone of voice is in keeping with your brand and appealing to your target customer.

Bullet points, short paragraphs, and images are good to break up the text. Make sure quotes and impressive statistics stand out, and cut down unnecessary words from quotes to keep them on-topic.

Case study example

At quintly, we use case studies to highlight the outstanding results that our customers have achieved. 

For inspiration, you can read our social media case study on Benefit Cosmetics and how they increased their engagement by 50% using our platform.

Let’s go through this case study step by step so you can use it for creating your own.

1. Write a headline and a summary

The headline must attract people’s attention straight away. We did this by mentioning the company name, and a specific result achieved: 50% increase in engagement.

We’ve then summarized the case study in one sentence providing a key takeaway of what our client was able to achieve.

2. Provide background on the company

Who is your client? What do they do, and who is their target customer? Giving some background on your client will help readers relate to them.

Here, you can see that we provide some basic stats relating to the company and what the brand believes in.

3. Highlight key results

Select a few of your most impressive metrics and make them stand out. We’ve chosen three metrics here that clearly demonstrate the success of our campaign.

4. Describe the problem or challenge

What wasn’t working well for your client before they contracted your services?

In our case study, we used quotes from Toto Haba, Senior Vice President of Global Digital at Benefit to highlight the critical need for the company to produce great content and engage its audience through social channels.

We explained the problems they were facing, and how using quintly helped them overcome them.

In your case, it could be that your clients don’t have enough expertise in data tracking to effectively analyze their social media campaigns and create new strategies.

There may be various ways in which you've helped your client get better results, so don’t be afraid to talk about them here, using direct quotes as much as possible.

5. Conclusion

You can close your report by summarizing once again the benefit that your clients has achieved. 

Or, you can use another quote from your client’s team, as we have done in our case study:

Collect and track data for your success stories

Collecting and analyzing data for case studies doesn’t have to be a hassle.

With quintly, you can automate the whole process and access a wealth of high-quality metrics and dashboards. 

Our tailor-made analytics solution for agencies can help you get amazing results for your clients on social media and have everything you need to put together your client testimonials. 

So start automating your social media analytics now!

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You know what else is in our pudding — besides the proof, that is? Awesomeness. Check out the case studies below to see examples of our success in helping small- medium-sized B2B companies build awesome businesses.

Lead Generation

Strategic Online Ads Drive Traffic and Boost ROI for ID Shop

m3 encouraged ID Shop to begin boosting its online retail presence organically through blog posts and social media that would drive traffic directly to the site.

deepening a digital identity: how we built online credibility for continental battery systems

Continental Battery Systems (CBS) began in 1932 as a small, family-owned battery manufacturer but has seen stunning growth in the past decade. Thanks to a series of mergers and acquisitions, it’s now the second-largest battery distributor in the U.S., with retail and distribution partners in every state.

Data-Driven Approach to Employee Engagement Case Study

Continental Battery Systems (CBS), founded in 1932 as a small, family-owned battery manufacturer, has grown exponentially over the past 10 years. CBS is now the second-largest battery distributor in the nation, with retail and distribution partners in every state.

SEO & Content Strategy Lead to 800% Increase in Web Traffic for ID Shop

A family-owned company with deep roots in the Southeastern United States, ID Shop supplies high-quality ID cards, credentials, badge holders, card printers and ID card products to customers across the country. The company prides itself on high-quality, American-made products designed to outperform and outlast the others in the field.

Aventis Systems White Paper Case Study

IT professionals engage only minimally online and are often reluctant to download content. However, after researching the particular needs of Aventis Systems’ audience, we wrote a technical white paper that drew 500 new visitors to the Aventis website.

Social Media

Aventis Systems Social Media Case Study

Aventis Systems was plagued by a stagnant social media strategy. Through research, a consistent posting schedule and engaging content, we were able to turn its social presence around and triple its transactions compared to the previous year.

Content Creation, Social Media

Earth 911 Case Study

Earth 911 wanted to reach an eco-conscious audience, but its fuzzy brand identity and inconsistent content strategy meant it wasn’t reaching the right people. By pairing quality content with an aggressive social media strategy, we were able to amass a social following of more than 350,000 for Earth 911 — resulting in 30 million annual page views and an email list of 70,000 subscribers.

Web Development

FlexXray Case Study

FlexXray was eager to position itself as a thought leader in the food inspection industry, but its marketing strategy wasn’t creating the desired results. Through in-depth research and a total revamp of its website and social media presence, we were able to increase leads and boost revenue.

Content Marketing

Texas Instruments Case Study

Texas Instruments Inc. needed an effective, efficient way to communicate its evolving HR policies to company leaders and managers around the globe but was held back by its limited platforms. With a new digital communication strategy and e-zine, we helped Texas Instruments reach thousands of company leaders.

Web Development, Social Media

US Dermatology Partners Case Study

US Dermatology Partners needed an online marketing campaign to spread awareness, increase revenue and book appointments for its newly acquired offices but was unsure where to start. With a website redesign and robust social media strategy, we helped US Dermatology Partners bring in more than $140,000 in revenue in just six months.

Content Creation, Content Promotion

Barron Designs Case Study

Barron Designs wanted a unique and innovative way to reach out to prospective buyers and introduce them to its line of faux wood, stone and brick home products. We launched a “What’s Your Design Style?” quiz that has not only attracted new customers, but sparked interest that provided monthly sales exceeding the previous three months of quiz-related revenue.

SEO, Web Development

ID Shop Case Study

A respected name in the badge and credential industry, ID Shop was looking to create a stronger online presence and increase online sales. With a robust website redesign and strategic SEO optimization, we helped ID Shop’s organic revenue improve 121% over the previous year.

Lead Generation, Content Promotion

True Texas Benefits Case Study

As an independent brokerage firm that provides insurance benefits packages to small, local businesses, True Texas Benefits found it difficult to stand out from larger, more established insurance firms. We created a better website presence by establishing a blog and launching a lead-gen e-book campaign, which has helped the company achieve a dramatic uptick in traffic and qualified leads.

PPC Advertising, SEO

Rainbow Muffler & Brake Case Study

With six locations throughout the greater Cleveland area, Rainbow Muffler & Brake wanted to establish itself as the region’s expert in automotive repair. The company wanted to drive web traffic to its sites and Facebook page, and to increase the number of phone calls it received each month. By focusing on Rainbow’s website, pay-per-click (PPC) advertising and SEO, we have increased web traffic by more than 5,873% in the past four years.

Aventis Systems Campaign Case Study

Even with a large social media following, Aventis Systems was experiencing minimal engagement. Through the creation of an online photo-sharing contest called #TidyIT, we helped Aventis exceed its social engagement goal by 200%.

WEB DEVELOPMENT

The Dallas Morning News Case Study

The Dallas Morning News had a health section with no focal point and minimal structure. We reorganized the site, revamped the content and improved the navigation so visitors could find information that was relevant to them, resulting in an increase in visitors and ad sales.

Health Wellness Alliance Case Study

The Health and Wellness Alliance for Children was having trouble reaching its desired audience due to a scattered marketing strategy. We repositioned the brand, defined its key audience segments and created a comprehensive marketing plan — resulting in a 500% increase in traffic by year’s end.

Mended Hearts Case Study

Mended Hearts, the world’s largest and oldest peer-to-peer cardiovascular patient-support network, struggled to create a clear editorial voice. We transformed their magazine by replacing canned content with original, patient-focused articles that engaged its audience — and we won several awards in the process.

WEB DEVELOPMENT, LEAD GENERATION

MIC Case Study

When the COVID-19 pandemic hit, Medical Informatics Corp. (MIC) was in a unique position to address patient-monitoring needs in hospitals across the nation with its innovative Sickbay program. In less than a month, we created and deployed a new website, white papers and an email campaign to spread awareness — resulting in over $1 million in projected revenue.

LEAD GENERATION

Minnesota Re-Bath Case Study

Minnesota Re-Bath wanted an online marketing campaign to increase its lead-gen numbers, but its weak online presence stood in the way. With the creation of a downloadable e-book and a Google AdWords campaign, we built a successful strategy that resulted in revenue growth.

VIDEOGRAPHY, CONTENT DEVELOPMENT

Operation Texas Shield Case Study

Operation Texas Shield needed a campaign to help raise awareness about sex trafficking prevention. We created a professional video and other marketing collateral that Operation Texas Shield has successfully used in presentations to its audience, resulting in more than 70,000 views.

CONTENT CREATION, WEB DEVELOPMENT

PMUSA Case Study

Prestigious Maintenance USA wanted to position itself as an industry leader, but struggled with consistent and effective marketing communication and brand positioning. By rebuilding the company’s website and developing a robust content strategy, we were able to increase PMUSA’s online visibility and help it earn award-winning recognition.

BRANDING, SOCIAL MEDIA

Smith System Case Study

Smith System was concerned that its image and messaging were outdated and ineffective at reaching its target audience of professional drivers. We substantially refreshed the look and feel of Smith System’s brand, website and social media marketing, resulting in an expanding audience and over $1 million in revenue.

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Top 5 Social Media Case Study Templates with Examples and Samples

Abhishek Tuteja

In the bustling digital cosmos, where fortunes are forged and brands rise like constellations, social media stands as the celestial stage for modern success stories. Harnessing the mercurial power of this boundless realm demands a masterful blend of artistry and data-driven strategy. Enter the world of social media case study PPT templates—the alchemical blueprint behind groundbreaking campaigns.

Picture this: A small artisanal chocolate company, nestled in a quaint corner of a bustling city, dared to dream beyond its brick-and-mortar confines. By harnessing the potential of the best social media presentations, they transcended geographical barriers and reached chocolate connoisseurs across the globe. Their mouthwatering visuals and tantalizing tales of cocoa craftsmanship set hearts aflutter, igniting a frenzy of shares and retweets that skyrocketed their humble brand into a worldwide sensation.

Needless to say, the power of a captivating presentation cannot be underestimated. A well-crafted case study PPT (PowerPoint) template serves as the storyteller's canvas—a medium that elevates a mundane marketing report into a captivating saga of triumph.

With 4.48 billion global social media users awaiting your company’s narrative, embark on a voyage of discovery with us in this piece of writing. 

Join us as we unlock the vault of the 5 best social media case studies PPT templates, empowering you to shape your odyssey of digital conquest.

Template 1- Business Case Study Summary on Social Media Marketing Template

Presenting our content-ready template designed to provide an alluring backdrop for any subject matter. Elevate your presentations and exude an air of professionalism, making you appear as a seasoned presentation virtuoso. Within this set of slides, you will find a comprehensive exploration of crucial topics, including the well-thought-out Approach, invaluable Recommendations, and prevailing Challenges faced in the realm of social media marketing. Instilled with versatility, this PowerPoint presentation is readily available for instant download, ensuring the utmost convenience and efficiency in customization, tailored to your specific needs.

Are you ready to seize the opportunity to impress and captivate with this remarkable PowerPoint template? Download now!

Download this template here

Template 2- Social Media Business Case Study Template

Here is another captivating and highly effective template to help you outline actionable strategies for your company. This well-crafted template strikes the perfect balance between clarity and concise expression, providing an explicit and visually engaging showcase for your transportation marketing case study. Tailored for entrepreneurs seeking to articulate their objectives to their esteemed employees, this professionally designed transportation marketing PPT one-pager acts as a guiding compass, enabling you to demonstrate the best value delivery to your cherished customers. You can illustrate crucial campaign details, celebrity branding metrics, target market insights, and the campaign's resounding success, exemplified by the desired percentage numbers. Incorporating essential testing content and transcending the boundaries of mobile optimization to also encompass desktop, this PPT template empowers you to deliver a gripping presentation that will undoubtedly captivate your audience's attention. Download this template now and make your mark in the world of transportation marketing.

Download here

Template 3- Case Study for Social Media Marketing Proposal Template

Introducing this premium PPT slide - a powerful and professionally designed presentation that is sure to leave a lasting impact on your audience. With a seamless one-stage process, this template covers critical aspects such as Technology, Communication, Planning, Strategy, and Marketing, all meticulously laid out to convey your proposal with utmost clarity and precision. This ready to use PowerPoint presentation offers unparalleled flexibility, empowering you to customize every element to match your unique requirements. Further, you can embrace creativity by replacing or removing icons, tailoring each slide to perfectly align with your message - a vast collection of icons awaits you to select the most fitting ones. Download this masterpiece now to captivate your audience and make a remarkable impression. Leave no room for mediocrity; instead, impress your stakeholders and win hearts with this actionable PowerPoint slide.

Template 4- Bi-fold Social Media Business Case Study Template 

Showcasing this remarkable PPT template to help you discover how successful brands strategize, engage, and convert their audience effectively. Dive into real-world examples, gaining valuable insights into content creation, posting schedules, and audience targeting using this PowerPoint slide. Uncover the secrets behind viral campaigns, follower growth, and brand loyalty. Whether you're a seasoned marketer or a budding entrepreneur, this template empowers you to fine-tune your social media approach and stay ahead of the competition. Elevate your digital presence, boost your ROI, and harness the full impact of social media through data-driven analysis and actionable takeaways provided in this invaluable resource.

Download the PPT Template here

Template 5- Case Study for Celebrity Template

Last, but not least, leverage the power of social media for celebrity branding with our specialized case study template. Gain exclusive access to real-world examples of successful collaborations between influencers and celebrities, exploring how they authentically connect with their audience and amplify brand reach. Uncover the strategies behind engaging content, influencer partnerships, and audience segmentation that elevate a celebrity's digital presence. This template offers in-depth analysis of campaigns that have driven massive follower growth, increased brand loyalty, and boosted product endorsements. Whether you're a brand looking to partner with a celebrity or a public figure aiming to optimize your social media impact, this template is your ultimate guide to effective celebrity branding.

Time to Elevate Your Presentation Game

Armed with the best social media case study PPT templates, your presentations are bound to transcend the norms of ordinary storytelling and ascend to captivating visual journeys that leave an indelible mark on your audience. Download any or all of these templates and harness the power of creativity and customization.

Step into the spotlight of presentation excellence and ignite curiosity, leaving your viewers yearning for more. The stage is set, and the templates await - unleash your creativity and captivate the world with the best social media case study PPT templates.

And if you are looking to rule the digital realm, then you may check out our comprehensive guide of 10 Best Digital Marketing Templates . These will help you elevate your online presence for sure.

For managers and entrepreneurs, we have resources that will help you cast away the work ethics myths and lead you toward enlightenment. Do take a look at our well-crafted list of Must-Have Corporate Ethics Case Study Examples with Templates and Samples .

FAQs on Social Media Case Study

What is a social media case study.

A social media case study is an in-depth analysis of a real-world social media marketing campaign or branding effort. It examines how brands, influencers, or individuals leveraged platforms to achieve specific objectives. These studies showcase strategies, challenges faced, and outcomes, encompassing goals, target audience, content, influencers, metrics, and impact on brand awareness, acquisition, and conversion rates. Valuable resources for marketers and businesses seeking social media optimization, case studies provide insights into effective tactics and best practices. By learning from successful campaigns, individuals can glean valuable knowledge to enhance their own social media endeavors and capitalize on the power of these platforms.

How do you introduce a case study on social media?

Introducing a case study on social media involves setting the stage, providing context, and outlining the purpose and objectives of the study. Here's a step-by-step guide on how to do it effectively:

• Start with a compelling title : Begin by giving your case study a clear and attention-grabbing title that highlights the key focus of the study.
• Provide a brief overview : In a few sentences, introduce the subject of the case study, whether it's brand, company, influencer, or celebrity involved in a social media campaign.
• State the objectives : Clearly outline the goals and objectives of the case study. What specific aspects of social media marketing or branding are being analyzed?
• Explain the importance : Highlight why this particular case study is relevant and significant in the context of social media marketing, industry trends, or specific challenges faced.
• Set the context : Briefly explain the background of the subject and the social media platforms they use. Mention any notable achievements or challenges they have encountered in their social media journey.
• Mention the methodology : Provide a brief overview of the research methodology used in the case study. This may include data sources, analysis tools, and any primary research conducted.
• Tease the results : Give a glimpse of the key findings or outcomes of the case study to generate interest and keep readers engaged.
• Discuss the structure : Briefly outline the sections or key areas covered in the case study, such as campaign strategies, content creation, influencer partnerships, etc.
• Emphasize actionable insights : Mention that the case study will offer valuable insights and actionable takeaways that can be applied to other social media strategies.
• Conclude with an invitation : Encourage readers to dive into the case study to learn more and explore the successful social media tactics employed by the subject.

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(From left) CAS Interim Dean Magali Michael with panelists Alex Mahadeven ( director of MediaWise at the Poynter Institute),  Julia Saad (mass communications senior and news editor of the USF Oracle), Aya Diab (doctoral communications student and Tampa Bay Times reporter), and Dr. Josh Scacco ( associate professor in the Department of Communication and director of the Center for Sustainable Democracy) . (Photo by Corey Lepak)

Democracy and Citizenship Series explores challenges and opportunities in today’s media landscape

• Anna Mayor, USF College of Arts and Sciences
• April 22, 2024

Community Engagement , Events

The USF College of Art and Sciences (CAS) held a panel discussion on the challenges 21st century media faces and how news can meet modern community needs so that it reaches new generations of information consumers.

Alex Mahadeven (right) talks with Julia Saad (left) and Aya Diab (middle) (Photo by Corey Lepak)

Julia Saad, a senior mass communications student and news editor of The Oracle , moderated the discussion, which was co-sponsored by the Center for Sustainable Democracy and the Humanities Institute .

Panelists included Alex Mahadevan, director of MediaWise at the Poynter Institute, and Aya Diab, a USF communication doctoral student and Tampa Bay Times journalist.

The discussion, “The Future of News: Challenges and Opportunities for a 21st Century Media System,” was held April 2 at C.W. Bill Young Hall.

“[The panelists] are engaging in the very difficult work of ensuring communities get quality information and that is what sustains democracies and ensures that people have the necessary tools to make informed decisions,” said Dr. Joshua Scacco , associate professor in the Department of Communication and director of the CSD.

The panelists emphasized how a changing media landscape means changes in how news is shared, especially as social media use rises and attention spans decrease.

“You have to be really engaging at first [with media]. Now, in terms of how to stay factual and tell the whole story in 30 seconds, that is very hard,” explained Mahadaven. “The majority of misinformation out there starts because people are only consuming 10 seconds of a video and you cannot tell the entire context or entire story of what’s happening in 10 to 30 seconds. Our challenge, your challenge, as an audience editor is essentially to try to break up the story into bits and pieces.”

Both panelists agree, treating engaging and easy-to-consume content is going to be key for the future of media.

Students attending the event were able to fulfill the opportunity for rigorous debate as mandated by the State of Florida Civics Literacy graduation requirement. (Photo by Corey Lepak)

“One of the many things that I like about my job is experimenting and being creative,” Diab said. “So, for example, if I’m covering a story about real estate and it has a geographical element to it, I try to visualize that in a map instead of telling people—ok, here’s a block of text that no one wants to read.”

Mahadaven added that user-generated content and the rise of artificial intelligence are other factors molding a new media landscape.

He also added that while new media has allowed for the spread of information more quickly, it also is quick to spread misinformation much more quickly.

“People will just read the headline and think they have the depth of the story, so, like a like of stuff in the new information age, it cuts both ways,” Mahadaven said.

Learn more about attending future  Democracy and Citizenship Series  lectures.

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True crime podcasts are popular in the U.S., particularly among women and those with less formal education

True crime stands out as the most common topic of top-ranked podcasts in the United States, according to a new Pew Research Center study . So who, exactly, listens to true crime podcasts?

Pew Research Center conducted this analysis to explore U.S. adults’ views of and experiences with podcasts as a part of the news and information landscape.

To examine the ways Americans get news and information in a digital age, the Center surveyed 5,132 U.S. adults from Dec. 5 to 11, 2022. Everyone who completed the survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the  ATP’s methodology .

In the questionnaire, U.S. adults who said they are currently listening to at least one podcast were asked in an open-ended question to write in the name of the podcast that they listen to most. If respondents answered with the names of more than one podcast, only the first one was coded. In total, 1,563 open-end responses were coded.

Here are  the questions used  in the survey, along with responses, and  its methodology .

As part of the study, the Center also took a close look at key characteristics of top-ranked podcasts. Researchers identified these top podcasts by analyzing daily lists of the top 200 podcasts on Apple Podcasts and Spotify from April 1 to Sept. 30, 2022. The average chart position of each podcast that appeared on either list was calculated, and the top 300 podcasts from each site were included as top podcasts. Researchers identified 451 top podcasts by combining these lists so that podcasts that were among the top 300 on both sites were not counted twice.

A team of trained researchers then analyzed these 451 podcasts to determine podcast affiliation, topic, format and other key characteristics of each podcast. Additional data on episode length and frequency was analyzed after collecting data on all episodes published in 2022 through the Spotify and Apple Podcasts application programming interface.

Here are the detailed tables for this analysis of 451 top-ranked podcasts, and the methodology .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. This is the latest analysis in Pew Research Center’s ongoing investigation of the state of news, information and journalism in the digital age, a research program funded by The Pew Charitable Trusts, with generous support from the John S. and James L. Knight Foundation.

Overall, 34% of U.S. adults who have listened to a podcast in the past year say they regularly listen to podcasts about true crime, according to a 2022 Center survey . But some demographic groups are more likely than others to do so:

• Among U.S. podcast listeners, women are almost twice as likely as men to regularly listen to true crime podcasts (44% vs. 23%).
• Podcast listeners with less formal education are more likely than those with higher levels of education to listen to shows about true crime. Looking at podcast listeners who have a high school diploma or less, 45% regularly listen to true crime podcasts. A third of podcast listeners with some college education say the same, as do 27% of those who have at least a bachelor’s degree. This pattern persists even when accounting for age.
• While women are more likely to listen to true crime podcasts overall, women with lower levels of formal education are the most likely to do so. A majority (57%) of women with a high school diploma or less say they regularly listen to true crime podcasts, compared with 34% of men with the same education level and 36% of women with a college degree.
• Younger podcast listeners are more likely than the oldest listeners to report tuning in to shows about true crime. Among U.S. podcast listeners ages 18 to 29, 41% regularly listen to true crime podcasts. This compares with 15% of listeners ages 65 and older.

The Center’s new study finds that true crime is the most common topic among top-ranked podcasts – defined as those with the highest average daily rankings on Apple’s and Spotify’s lists of top podcasts in a six-month period in 2022. Almost a quarter (24%) of these top podcasts are primarily about true crime.

True crime podcasts are often investigations into murders, scandals and other criminal events. Serial, which helped to popularize the genre , is a series that provides in-depth investigations into particular crimes or events. Due to its popularity, Serial is often credited for drawing national attention to the conviction of Adnan Syed.

Other top-ranked podcasts in this genre include 20/20, Crime Junkie, Dateline NBC, and My Favorite Murder. Crime Junkie and Dateline NBC are among the most popular podcasts cited by podcast listeners who gave a name for the show they tune in to most – 1% named each of these podcasts.

While true crime is the most common topic among top-ranked podcasts, it is not the most popular topic Americans report listening to, according to the Center’s recent survey . About a third of podcast listeners in the United States (34%) say they regularly listen to podcasts about true crime.

Other topics – such as comedy (47%) and entertainment, pop culture and the arts (46%) – are more popular than true crime.

While the Center’s survey did not specifically ask why podcast listeners turn to specific topics such as true crime, we can look at the reasons that people said they listen to podcasts in general – and among those who said the podcast they listen to most is true crime.

Of those who said their main podcast is about true crime, the most common major reasons for listening were for entertainment (85%) and to have something to listen to while doing something else (84%). They were less likely to cite reasons like learning, hearing other people’s opinions, or staying up to date about current events.

Note: Here are the detailed tables for this analysis of 451 top-ranked podcasts, and the methodology . Here are the questions used for this analysis, and our survey methodology .

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Social Media Surveillance by the U.S. Government

A growing and unregulated trend of online surveillance raises concerns for civil rights and liberties.

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Social media has become a significant source of information for U.S. law enforcement and intelligence agencies. The Department of Homeland Security, the FBI, and the State Department are among the many federal agencies that routinely monitor social platforms, for purposes ranging from conducting investigations to identifying threats to screening travelers and immigrants. This is not surprising; as the U.S. Supreme Court has  said , social media platforms have become “for many . . . the principal sources for knowing current events, . . . speaking and listening in the modern public square, and otherwise exploring the vast realms of human thought and knowledge” — in other words, an essential means for participating in public life and communicating with others.

At the same time, this growing — and mostly unregulated — use of social media raises a host of civil rights and civil liberties concerns. Because social media can reveal a wealth of personal information — including about political and religious views, personal and professional connections, and health and sexuality — its use by the government is rife with risks for freedom of speech, assembly, and faith, particularly for the Black, Latino, and Muslim communities that are historically targeted by law enforcement and intelligence efforts. These risks are far from theoretical: many agencies have a track record of using these programs to target minority communities and social movements. For all that, there is little evidence that this type of monitoring advances security objectives; agencies rarely measure the usefulness of social media monitoring and DHS’s own pilot programs showed that they were not helpful in identifying threats. Nevertheless, the use of social media for a range of purposes continues to grow.

In this Q&A, we survey the ways in which federal law enforcement and intelligence agencies use social media monitoring and the risks posed by its thinly regulated and growing use in various contexts.

Which federal agencies use social media monitoring?

Many federal agencies use social media, including the  Department of Homeland Security  (DHS),  Federal Bureau of Investigation  (FBI),  Department of State  (State Department),  Drug Enforcement Administration  (DEA),  Bureau of Alcohol, Tobacco, Firearms and Explosives  (ATF),  U.S. Postal Service  (USPS),  Internal Revenue Service  (IRS),  U.S. Marshals Service , and  Social Security Administration  (SSA). This document focuses primarily on the activities of DHS, FBI, and the State Department, as the agencies that make the most extensive use of social media for monitoring, targeting, and information collection.

Why do federal agencies monitor social media?

Publicly available information shows that federal agencies use social media for four main — and sometimes overlapping — purposes. The examples below are illustrative and do not capture the full spectrum of social media surveillance by federal agencies.

Investigations : Law enforcement agencies, such as the FBI and some components of DHS, use social media monitoring to assist with criminal and civil investigations. Some of these investigations may not even require a showing of criminal activity. For example, FBI agents can open an “assessment” simply on the basis of an “authorized purpose,” such as preventing crime or terrorism, and without a factual basis. During assessments, FBI agents can carry out searches of publicly available online information. Subsequent investigative stages, which require some factual basis, open the door for more invasive surveillance tactics, such as the monitoring and recording of chats, direct messages, and other private online communications in real time.

At DHS, Homeland Security Investigations (HSI) — which is part of Immigration and Customs Enforcement (ICE) — is the Department’s “ principal investigative arm .” HSI  asserts  in its training materials that it has the authority to enforce any federal law, and relies on social media when conducting investigations on matters ranging from civil immigration violations to terrorism. ICE agents can look at publicly available social media content for purposes ranging from finding fugitives to gathering evidence in support of investigations to probing “potential criminal activity,” a “threat detection” function discussed below. Agents can also operate undercover online and monitor private online communications, but the circumstances under which they are permitted to do so are not publicly known.

Monitoring to detect threats:  Even without opening an assessment or other investigation, FBI agents can monitor public social media postings. DHS components from ICE to its intelligence arm, the Office of Intelligence & Analysis, also  monitor social media  — including specific individuals — with the goal of identifying potential threats of violence or terrorism. In addition, the FBI and DHS both engage private companies to conduct online monitoring of this type on their behalf. One firm, for example, was  awarded  a  contract  with the FBI in December 2020 to scour social media to proactively identify “national security and public safety-related events” — including various unspecified threats, as well as crimes — which have not yet been reported to law enforcement.

Situational awareness:  Social media  may   provide  an “ear to the ground” to help the federal government coordinate a response to breaking events. For example, a range of DHS components — from Customs and Border Protection (CBP) to the National Operations Center (NOC) to the Federal Emergency Management Agency ( FEMA ) — monitor the internet, including by keeping tabs on a broad list of websites and keywords being discussed on social media platforms and tracking information from sources like news services and local government agencies.  Privacy impact assessments  suggest there are few limits on the content that can be reviewed — for instance, the PIAs list a sweeping range of keywords that are monitored (ranging, for example, from “attack,” “public health,” and “power outage,” to “jihad”). The purposes of such monitoring include helping keep the public, private sector, and governmental partners informed about developments during a crisis such as a natural disaster or terrorist attack; identifying people needing help during an emergency; and knowing about “ threats or dangers ” to DHS facilities.

“Situational awareness” and “threat detection” overlap because they both involve broad monitoring of social media, but situational awareness has a wider focus and is generally not intended to monitor or preemptively identify specific people who are thought to pose a threat.

Immigration and travel screening:  Social media is  used to  screen and vet travelers and immigrants coming into the United States and even to monitor them while they live here. People applying for a range of immigration benefits  also undergo  social media checks to verify information in their application and determine whether they pose a security risk.

How can the government’s use of social media harm people?

Government monitoring of social media can work to people’s detriment in at least four ways: (1) wrongly implicating an individual or group in criminal behavior based on their activity on social media; (2) misinterpreting the meaning of social media activity, sometimes with severe consequences; (3) suppressing people’s willingness to talk or connect openly online; and (4) invading individuals’ privacy. These are explained in further detail below.

Assumed criminality:  The government may use information from social media to label an individual or group as a threat, including characterizing  ordinary activity  (like wearing a particular sneaker brand or making common hand signs) or social media connections as evidence of criminal or threatening behavior. This kind of assumption can have high-stakes consequences. For example, the NYPD  wrongly arrested  19-year-old Jelani Henry for attempted murder, after which he was denied bail and jailed for over a year and a half, in large part because prosecutors thought his “likes” and photos on social media proved he was a member of a violent gang. In another  case  of guilt by association, DHS officials barred a Palestinian student arriving to study at Harvard from entering the country based on the content of his friends’ social media posts. The student had neither written nor engaged with the posts, which were critical of the U.S. government. Black, Latino, and Muslim people are especially vulnerable to being falsely labeled threats based on social media activity, given that it is used to inform government decisions that are often already tainted by bias such as  gang determinations  and  travel screening  decisions.

Mistaken judgments:  It can be difficult to accurately interpret online activity, and the repercussions can be severe. In 2020, police in Wichita, Kansas  arrested  a teenager on suspicion of inciting a riot based on a mistaken interpretation of his Snapchat post, in which he was actually denouncing violence. British travelers were interrogated at Los Angeles International Airport and  sent back  to the U.K. due to a border agent’s misinterpretation of a joking tweet. And DHS and the FBI  disseminated  reports to a Maine-area intelligence-sharing hub warning of potential violence at anti-police brutality demonstrations based on fake social media posts by right-wing provocateurs, which were distributed as a warning to local police.

Chilling effects:  People are highly likely to  censor  themselves when they think they are being watched by the government, and this undermines everything from political speech to creativity to other forms of self-expression. The Brennan Center’s  lawsuit  against the State Department and DHS documents how the collection of social media identifiers on visa forms — which are then stored indefinitely and shared across the U.S. government, and sometimes with state, local, and foreign governments — led a number of international filmmakers to stop talking about politics and promoting their work on social media. They self-censored because they were concerned that what they said online would prevent them from getting a U.S. visa or be used to retaliate against them because it could be misinterpreted or reflect controversial viewpoints.

Loss of privacy:  A person’s  social media presence  — their posts, comments, photos, likes, group memberships, and so on — can collectively reveal their ethnicity, political views, religious practices, gender identity, sexual orientation, personality traits, and vices. Further, social media can reveal more about a person than they intend. Platforms’ privacy settings frequently change and can be difficult to navigate, and even when individuals keep information private it can be disclosed through the activity or identity of their connections on social media. DHS at least has recognized this risk, categorizing social media handles as “sensitive personally identifiable information” that could “result in substantial harm, embarrassment, inconvenience, or unfairness to an individual.” Yet the agency has failed to place robust safeguards on social media monitoring.

Who is harmed by social media monitoring?

While all Americans may be harmed by untrammeled social media monitoring, people from historically marginalized communities and those who protest government policies typically bear the brunt of suspicionless surveillance. Social media monitoring is no different.

Echoing the transgressions of the  civil rights era , there  are   myriad   examples  of the FBI and DHS using social media to surveil people speaking out on issues from racial justice to the treatment of immigrants. Both agencies have monitored Black Lives Matter activists. In 2017, the FBI  created  a specious terrorism threat category called “Black Identity Extremism” (BIE), which can be read to include protests against police violence. This category has been used to rationalize  continued   surveillance  of black activists, including monitoring of social media activity. In 2020, DHS’s Office of Intelligence & Analysis (I&A)  used  social media and other tools to target and monitor racial justice protestors in Portland, OR, justifying this surveillance by pointing to the threat of vandalism to Confederate monuments. I&A then  disseminated  intelligence reports on journalists reporting on this overreach.

DHS especially has  focused  social media surveillance on immigration activists, including those engaged in  peaceful protests  against the Trump administration’s family separation policy and others  characterized  as “anti-Trump protests.” From 2017 through 2020, ICE  kept tabs  on immigrant rights groups’ social media activity, and in late 2018 and early 2019, CBP and HSI  used   information  gleaned from social media in compiling dossiers and putting out travel alerts on advocates, journalists, and lawyers — including U.S. citizens — whom the government suspected of helping migrants south of the U.S. border.

Muslim, Arab, Middle Eastern, and South Asian communities have often been particular targets of the U.S. government’s  discriminatory  travel and immigration screening practices, including social media screening. The State Department’s collection of social media identifiers on visa forms, for instance,  came out  of President Trump’s Muslim ban, while  earlier  social media monitoring and collection programs focused disproportionately on people from predominantly Muslim countries and Arabic speakers.

Is social media surveillance an effective way of getting information about potential threats?

Not particularly. Broad social media monitoring for threat detection purposes untethered from suspicion of wrongdoing generates reams of useless information, crowding out information on — and resources for — real public safety concerns.

Social media conversations are difficult to interpret because they are often highly context-specific and can be riddled with slang, jokes, memes, sarcasm, and references to popular culture; heated rhetoric is also common. Government officials and assessments have repeatedly recognized that this dynamic makes it difficult to distinguish a sliver of genuine threats from the millions of everyday communications that do not warrant law enforcement attention. As the former acting chief of DHS I&A  said , “actual intent to carry out violence can be difficult to discern from the angry, hyperbolic — and constitutionally protected — speech and information commonly found on social media.” Likewise, a 2021  internal review  of DHS’s Office of Intelligence & Analysis noted: “[s]earching for true threats of violence before they happen is a difficult task filled with ambiguity.” The review observed that personnel trying to anticipate future threats ended up collecting information on a “broad range of general threats that did not meet the threshold of intelligence collection” and provided I&A’s law enforcement and intelligence customers with “information of limited value,” including “memes, hyperbole, statements on political organizations and other protected First Amendment speech.” Similar  concerns  cropped up with the DHS’s pilot programs to use social media to vet refugees.

The result is a high volume of false alarms, distracting law enforcement from investigating and preparing for genuine threats: as the FBI bluntly  put it , for example, I&A’s reporting practices resulted in “crap” being sent through one of its threat notification systems.

What rules govern federal agencies’ use of social media?

Some agencies, like the FBI, DHS, State Department and  IRS , have released information on the rules governing their use of social media in certain contexts. Other agencies — such as the ATF, DEA, Postal Service, and Social Security Administration — have not made any information public; what is known about their use of social media has emerged from media coverage, some of which has attracted  congressional   scrutiny . Below we describe some of what is known about the rules governing the use of social media by the FBI, DHS, and State Department.

FBI:  The main document governing the FBI’s social media surveillance practices is its  Domestic Investigations and Operations Guide  (DIOG), last made public in redacted form in 2016. Under the DIOG, FBI agents may review publicly available social media information prior to initiating any form of inquiry. During the lowest-level investigative stage, called an assessment (which requires an “authorized purpose” such as stopping terrorism, but no factual basis), agents may also log public, real-time communications (such as public chat room conversations) and work with informants to gain access to private online spaces, though they may not record private communications in real-time.

Beginning with “preliminary investigations” (which require that there be “information or an allegation” of wrongdoing but not that it be credible), FBI agents may monitor and record private online communications in real-time using informants and may even use false social media identities with the approval of a supervisor. While conducting full investigations (which require a reasonable indication of criminal activity), FBI agents may use all of these methods and can also get probable cause warrants to conduct wiretapping, including to collect private social media  communications .

The DIOG does restrict the FBI from probing social media based  solely  on “an individual’s legal exercise of his or her First Amendment rights,” though such activity can be a substantial motivating factor. It also requires that the collection of online information about First Amendment-protected activity be connected to an “authorized investigative purpose” and be as minimally intrusive as reasonable under the circumstances, although it is not clear how adherence to these standards is evaluated.

DHS:  DHS policies can be pieced together using a combination of legally mandated disclosures — such as privacy impact assessments and data mining reports — and publicly available policy guidelines, though the amount of information available varies. In 2012, DHS published  a   policy  requiring that components collecting personally identifiable information from social media for “operational uses,” such as investigations (but not intelligence functions), implement basic guidelines and training for employees engaged in such uses and ensure compliance with relevant laws and privacy rules. Whether this policy has been holistically implemented for “operational uses” of social media across DHS remains unclear. However, the Brennan Center has obtained a number of templates describing how DHS components use social media, created pursuant to the 2012 policy, through the Freedom of Information Act.

In practice, DHS policies are generally permissive. The examples below illustrate the ways in which various parts of the Department use social media.

• ICE agents monitor social media for purposes ranging from situational awareness and criminal intelligence gathering to support for investigations. In addition to engaging private companies to monitor social media, ICE agents  may collect  public social media data whenever they determine it is “relevant for developing a viable case” and “supports the investigative process.”
• Parts of DHS, including the National Operations Center (NOC) (part of the Office of Operations Coordination and Planning ( OPS )), Federal Emergency Management Agency ( FEMA ), and Customs and Border Protection ( CBP ), use social media monitoring for situational awareness. The goal is generally not to “seek or collect” personally identifiable information. DHS may do so in “in extremis situations,” however, such as when serious harm to a person may be imminent or there is a “credible threat[] to [DHS] facilities or systems.” NOC’s situational awareness operations are not covered by the 2012 policy; other components carrying out situational awareness monitoring must create a but may receive an exception from the broader policy with the approval of DHS’s Chief Privacy Officer.
• DHS’s U.S. Citizenship and Immigration Services ( USCIS ) uses social media to verify the accuracy of materials provided by applicants for immigration benefits (such as applications for refugee status or to become a U.S. citizen) and to identify fraud and threats to public safety. USCIS says it only looks at publicly available information and that it will respect account holders’ privacy settings and refrain from direct dialogue with subjects, though staff may use fictitious accounts in certain cases, including when “overt research would compromise the integrity of an investigation.”
• DHS’s Office of Intelligence & Analysis (I&A), as a member of the Intelligence Community, is not covered by the 2012 policy. Instead it operates under a separate set of  guidelines  — pursuant to Executive Order 12,333, issued by the Secretary of Homeland Security and approved by the Attorney General — that govern its management of information collected about U.S. persons, including via social media. The office incorporates social media into the open-source intelligence reports it produces for federal, state, and local law enforcement; these reports provide threat warnings, investigative leads, and referrals. I&A personnel  may  collect and retain social media information on U.S. citizens and green card holders so long as they reasonably believe that doing so supports a national or departmental mission; these missions are broadly defined to include addressing homeland security concerns. And they may disseminate the information further if they believe it would help the recipient with “lawful intelligence, counterterrorism, law enforcement, or other homeland security-related functions.”

State Department.  The Department’s policies covering social media monitoring for visa vetting purposes are not publicly available. However,  public   disclosures  shed some light on the rules consular officers are supposed to follow when vetting visa applicants using social media. For example, consular officers are not supposed to interact with applicants on social media, request their passwords, or try to get around their privacy settings — and if they create an account to view social media information, they “must abide by the contractual rules of that service or platform provider,” such as Facebook’s real name policy. Further, information gleaned from social media must not be used to deny visas based on protected characteristics (i.e., race, religion, ethnicity, national origin, political views, gender or sexual orientation). It is supposed to be used only to confirm an applicant’s identity and visa eligibility under criteria set forth in U.S. law.

Are there constitutional limits on social media surveillance?

Yes. Social media monitoring may violate the First or Fourteenth Amendments. It is well established that public posts receive constitutional protection: as the investigations guide of the Federal Bureau of Investigation recognizes, “[o]nline information, even if publicly available, may still be protected by the First Amendment. Surveillance is clearly unconstitutional when a person is specifically  targeted  for the exercise of constitutional rights protected by the  First Amendment  (speech, expression, association, religious practice) or on the basis of a characteristic protected by the  Fourteenth Amendment  (including race, ethnicity, and religion). Social media monitoring may also violate the First Amendment when it burdens constitutionally protected activity and does not contribute to a legitimate government objective. Our  lawsuit  against the State Department and DHS ( Doc Society v. Blinken ), for instance, challenges the collection, retention, and dissemination of social media identifiers from millions of people — almost none of whom have engaged in any wrongdoing — because the government has not adequately justified the screening program and it imposes a substantial burden on speech for little demonstrated value. The White House office that reviews federal regulations noted the latter point — which a DHS Inspector General  report  and  internal reviews  have also underscored  — when it  rejected , in April 2021, DHS’s proposal to collect social media identifiers on travel and immigration forms.

Additionally, the  Fourth Amendment  protects people from “unreasonable searches and seizures” by the government, including searches of data in which people have a “reasonable expectation of privacy.” Judges have  generally   concluded  that content posted publicly online cannot be reasonably expected to be private, and that police therefore do not need a warrant to view or collect it. Courts are increasingly recognizing, however, that when the government can collect far more information — especially information revealing sensitive or intimate details — at a far lower cost than traditional surveillance, the Fourth Amendment  may protect  that data. The same is true of social media monitoring and the use of powerful social media monitoring tools, even if they are employed to review publicly available information.

Are there statutory limits on social media surveillance?

Yes. Most notably, the  Privacy Act  limits the collection, storage, and sharing of personally identifiable information about U.S. citizens and permanent residents (green card holders), including social media data. It also bars, under most circumstances, maintaining records that describe the exercise of a person’s First Amendment rights. However, the statute contains an exception for such records “within the scope of an authorized law enforcement activity.” Its coverage is limited to databases from which personal information can be retrieved by an individual identifier like a name, social security address, or phone number.

Additionally, federal agencies’ collection of social media handles must be authorized by law and, in some cases, be subject to public notice and comment and justified by a reasoned explanation that accounts for contrary evidence.  Doc Society v. Blinken , for example, alleges that the State Department’s collection of social media identifiers on visa forms violates the Administrative Procedure Act (APA) because it exceeds the Secretary of State’s statutory authority and did not consider that prior social media screening pilot programs had failed to demonstrate efficacy.

Is the government’s use of social media consistent with platform rules?

Not always. Companies do not bar government officials from making accounts and looking at what is happening on their platforms. However, after the ACLU  exposed  in 2016 that third-party social media monitoring companies were pitching their services to California law enforcement agencies as a way to monitor protestors against racial injustice,  Twitter ,  Facebook , and Instagram changed or clarified their rules to prohibit the use of their data for surveillance (though the actual  application  of those rules can be murky).

Additionally, Facebook has a  policy  requiring users identify themselves by their “real names,” with no exception for law enforcement. The FBI and other federal law enforcement agencies permit their agents to use false identities notwithstanding this rule, and there have been documented instances of other law enforcement departments  violating  this policy as well.

How do federal agencies share information collected from social media, and why is it a problem?

Federal agencies may share information they collect from social media across all levels of government and the private sector and will sometimes even disclose data to foreign governments (for instance,  identifiers  on travel and immigration forms). In particular, information is shared domestically with state and local law enforcement, including through fusion centers, which are post-9/11 surveillance and intelligence hubs that were intended to facilitate coordination among federal, state, and local law enforcement and private industry. Such unfettered data sharing magnifies the risks of abusive practices.

Part of the risk stems from the dissemination of data to actors with a documented history of discriminatory surveillance, such as fusion centers. A 2012 bipartisan Senate investigation  concluded  that fusion centers have “yielded little, if any, benefit to federal counterterrorism intelligence efforts,” instead producing reams of low-quality information while labeling Muslim Americans engaging in innocuous activities, such as voter registration, as potential threats. More recently,  fusion centers  have been  caught   monitoring  racial and social justice organizers and protests and  promoting  fake social media posts by right-wing provocateurs as credible intelligence regarding potential violence at anti-police brutality protests. Further, many police departments that get information from social media through fusion centers (or from federal agencies like the FBI and DHS directly) have a  history  of targeting and surveilling minority communities and activists, but lack basic policies that govern their use of social media. Finally, existing agreements  permit  the U.S. government to share social media data — collected from U.S. visa applicants, for example — with repressive foreign governments that are known to retaliate against online critics.

The broad dissemination of social media data amplifies some of the harms of social media monitoring by eliminating context and safeguards. Under some circumstances, a government official who initially reviews and collects information from social media may better understand — from witness interviews, notes of observations from the field, or other material obtained during an investigation, for example — its meaning and relevance than a downstream recipient lacking this background. And any safeguards the initial agency places upon its monitoring and collection — use and retention limitations, data security protocols, etc. — cannot be guaranteed after it disseminates what has been gathered. Once social media is disseminated, the originating agency has little control over how such information is used, how long it is kept, whether it could be misinterpreted, or how it might spur overreach.

Together, these dynamics amplify the harms to free expression and privacy that social media monitoring generates. A qualified and potentially unreliable assessment based on social media that a protest could turn violent or that a particular person poses a threat might easily turn into a justification for policing that protest aggressively or arresting the person, as illustrated by the examples above. Similarly, a person who has applied for a U.S. visa or been investigated by federal authorities, even if they are cleared, is likely to be wary of what they say on social media well into the future if they know that there is no endpoint to potential scrutiny or disclosure of their online activity. Formerly, one branch of DHS I&A had a  practice  of redacting publicly available U.S. person information contained in open-source intelligence reports disseminated to partners because of the “risk of civil rights and liberties issues.” This practice was an apparent justification for removing pre-publication oversight to identify such issues, which implies that DHS recognized that information identifying a person could be used to target them without a legitimate law enforcement reason.

What role do private companies play, and what is the harm in using them?

Both  the   FBI  and  DHS  have reportedly hired private firms to help conduct social media surveillance, including to help identify threats online. This raises concerns around transparency and accountability as well as effectiveness.

Transparency and accountability:  Outsourcing surveillance to private industry obscures how monitoring is being carried out; limited information is available about relationships between the federal government and social media surveillance contractors, and the contractors, unlike the government, are not subject to freedom of information laws. Outsourcing also weakens safeguards because private vendors may not be subject to the same legal or institutional constraints as public agencies.

Efficacy:  The most ambitious tools use artificial intelligence with the goal of making judgments about which threats, calls for violence, or individuals pose the highest risk. But doing so reliably is beyond the capacity of both humans and existing technology, as more than 50 technologists  wrote  in opposing an ICE proposal aimed at predicting whether a given person would commit terrorism or crime. The more rudimentary of these tools look for specific words and then flag posts containing those words. Such flags are overinclusive, and garden-variety content will regularly be  elevated . Consider how the word “extremism,” for instance, could appear in a range of news articles, be  used  in reference to a friend’s strict dietary standards, or arise in connection with discussion about U.S. politics. Even the best Natural Language Processing tools, which attempt to ascertain the meaning of text, are prone to  error , and fare particularly  poorly  on speakers of non-standard English, who may more frequently be from minority communities, as well as speakers of languages other than English. Similar  concerns  apply to mechanisms used to flag images and videos, which generally lack the context necessary to differentiate a scenario in which an image is used for reporting or commentary from one where it is used by a group or person to incite violence.

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Flowing Cents

10 Case Studies in Media Responsibility

Posted: April 18, 2024 | Last updated: April 20, 2024

Press Media plays a crucial role in our day-to-day life. It makes us aware of our surroundings, educates & informs us. Sometimes, it acts as the voice of the oppressed & sometimes the voice of democracy. Media can easily shape people’s narratives, and it is, therefore, its responsibility to stay unbiased. Here are the top ten corporate social responsibilities of Media that are extracted from case studies:

1. Freedom of Speech & Information

Freedom of speech & information is not only an individual’s right but also Press Media’s. They aren’t present to give their opinions but rather to provide the opinions of the masses. It should provide diverse viewpoints for the audience to understand events from different perspectives. It needs to become the public’s voice & broadcast their needs & social/national issues.

2. Counter Verify News

Like Winston Churchill said, “With great power comes great responsibility.” Media houses must verify and counter-verify news from their sources, or it may mislead the public. This can be made possible by talking to spokespersons, conducting thorough investigations & fact-checking information before reporting. It is done to ensure accuracy & build credibility in the industry.

3. Avoid Hatred or False Spreading

News media is trained to be respectful & empathetic when reporting tragic events like loss of lives. Sometimes, the Media need to report low-key disgraceful events, i.e., Riots, to avoid protests and massacres to maintain peace. This is done to prevent public aggression that often arises with tensions in the country like protests & social issues. But, the media must spread news & tell the public the actual stats.

4. Security to Sources

Breaking news can take months & years to form. It requires extensive research & a drive of curiosity to look for minute details for which the Press hires sources to get any new information quickly. These sources operate undercover in hazardous areas & are often seen assassinated for providing news to the press media. So, it is their responsibility to provide their sources with security & ensure their secrecy.

5. Invasion of Privacy

Every person has a personal space that no one has the right to breach. Media shouldn’t enter someone’s private life to get juicy gossip to report & implement ethical journalism. It is unethical to spy on people to get spicy gossip news to attract eyeballs. Celebrities are public figures, but they also have a personal space that the Media must respect & continue to perform their jobs.

6. Reply & Correction

We’re humans, and it is human nature to err. If the media publishes any false news mistakenly, then it’s their responsibility to step up & accept it. Reply to the general public and ensure the correction of mistakes. Since they are present to provide the opinions of the masses, they should be free to be held accountable for any wrongdoings. 

7. Confidentiality

The Press cannot take any criminal’s name or personal details from the media regulatory authority. It is because they cannot decide to defame any person or organization. Only law & order can determine the punishment of such a person. It can also impact the mental health of the family members.

8. Respectful to All Ethnicities

Media is encouraged to integrate all ethnicities. Avoid shaping a narrative against any community or religion that could ruin national & social interests. With freedom of speech, it is the Media’s responsibility to stay neutral. It is also against the law & regulations to run campaigns for ethnic cleansing and infuriating people against each other. They should promote equality & anti-discrimination.

9. Copyright

Sometimes, the media violates ethical guidelines and broadcasts online creators’ content without their permission & any credit is given. The role of the media is crucial to make people aware of what is happening in their surroundings. Instead of reporting content with just a Google search, they must ensure plagiarism-free content and embrace originality.

10. Endorsements & Promotions

Business people often buy media channels & merge them into their conglomerate to make people hear what they want. This also provides free advertisement for their company’s products, harming consumers’ interests. Avoid directly endorsing any product or service. People should instead differentiate from people who promote ethical journalism through their work.

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Judge in Trump case orders media not to report where potential jurors work

A jury of 12 people was seated Thursday in former President Donald Trump’s history-making hush money trial. (AP Production: Javier Arciga)

Former President Donald Trump, flanked by attorneys Todd Blanche and Emil Bove, appears at Manhattan criminal court during jury selection in New York, Thursday, April 18, 2024. (Jabin Botsford/The Washington Post via AP, Pool)

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Members of the media gather outside Manhattan Criminal Court, Tuesday, April 16, 2024, in New York. Former President Donald Trump will return to court as a judge works to find a panel of jurors who will decide whether the former president is guilty of criminal charges alleging he falsified business records to cover up a sex scandal during the 2016 campaign. (AP Photo/Yuki Iwamura)

In this courtroom sketch, former President Donald Trump sits beside his lawyer Todd Blanche on the second day of jury selection in his criminal trial in Manhattan criminal court in New York on Tuesday, April 16, 2024. (Christine Cornell via AP Pool)

Former President Donald Trump holds up news clippings as he speaks following his trial at Manhattan criminal court in New York on Thursday, April 18, 2024. (Timothy A. Clary/Pool Photo via AP)

Former President Donald Trump speaks with the media while holding news clippings following his trial at Manhattan criminal court in New York on Thursday, April 18, 2024. (Brendan McDermid/Pool Photo via AP)

Former president Donald Trump, motions to a crowd after visiting a bodega, Tuesday, April 16, 2024, who’s owner was attacked last year in New York. Fresh from a Manhattan courtroom, Donald Trump visited a New York bodega where a man was stabbed to death, a stark pivot for the former president as he juggles being a criminal defendant and the Republican challenger intent on blaming President Joe Biden for crime. Alba’s attorney, Rich Cardinale, second from left, and Fransisco Marte, president of the Bodega Association, looked on. (AP Photo/Yuki Iwamura)

Former president Donald Trump, talks to members of the media while visiting a bodega, Tuesday, April 16, 2024, who’s owner was attacked last year in New York. Fresh from a Manhattan courtroom, Donald Trump visited a New York bodega where a man was stabbed to death, a stark pivot for the former president as he juggles being a criminal defendant and the Republican challenger intent on blaming President Joe Biden for crime. Alba’s attorney, Rich Cardinale, second from left, and Fransisco Marte, president of the Bodega Association, looked on. (AP Photo/Yuki Iwamura)

NEW YORK (AP) — The judge in Donald Trump’s hush money trial ordered the media on Thursday not to report on where potential jurors have worked and to be careful about revealing information about those who will sit in judgment of the former president .

Judge Juan Merchan acted after one juror was dismissed when she expressed concerns about participating in the trial after details about her became publicly known.

What to know about Trump’s hush money trial:

• Follow AP’s live coverage of opening statements.
• Trump will be first ex-president on criminal trial. Here’s what to know about the hush money case.
• A jury of his peers: A look at how jury selection will work in Donald Trump’s first criminal trial .
• Trump is facing four criminal indictments, and a civil lawsuit. You can track all of the cases here.

The names of the jurors are supposed to be a secret, but the dismissed juror told Merchan she had friends, colleagues and family members contacting her to ask whether she was on the case. “I don’t believe at this point I can be fair and unbiased and let the outside influences not affect my decision-making in the courtroom,” she said.

Merchan then directed journalists present in the courthouse not to report it when potential jurors told the court their specific workplaces, past or present. That put journalists in the difficult position of not reporting something they heard in open court.

Some media organizations were considering whether to protest having that onus placed on them. Generally, the First Amendment of the U.S. Constitution bars judges from ordering journalists not to disclose what they hear and see in courtrooms open to the public, though there are exceptions, such as when military security is at stake.

New York criminal defense lawyer Ron Kuby said that while judges typically can’t control what the media reports, other options are available to protect juror anonymity, including restricting what reporters see and hear in the courtroom.

“There are actions the judge could take,” he said. “Courts have extraordinary powers to protect jurors from tampering and intimidation. It is really where a court’s power is at its peak.”

The court action underscored the difficulty of trying to maintain anonymity for jurors in a case that has sparked wide interest and heated opinions, while lawyers need to sift through as much information as possible in a public courtroom to determine who to choose.

Despite the setback, 12 jurors were seated by the end of Thursday for the historic trial. Trump is charged with falsifying his company’s business records to cover up an effort during the 2016 presidential election campaign to squash negative publicity about alleged marital infidelity. Part of the case involves a $130,000 payment made to porn actor Stormy Daniels to prevent her from making public her claims of a sexual meeting with Trump years earlier. Trump has denied the encounter.

New York state law requires trial attorneys to get the names of jurors, but the judge has ordered the lawyers in Trump’s case not to disclose those names publicly. The jurors’ names haven’t been mentioned in court during three days of jury selection.

Still, enough personal information about the jurors was revealed in court that people might be able to identify them anyway.

Some news organizations described details including what Manhattan neighborhoods potential jurors lived in, what they did for a living, what academic degrees they had earned, how many children they had, what countries they grew up in and what their spouses did for a living.

On Fox News Channel Wednesday night, host Jesse Watters did a segment with a jury consultant, revealing details about people who had been seated on the jury and questioning whether some were “stealth liberals” who would be out to convict Trump.

Besides his order about employment history, Merchan said he was asking the media to “simply apply common sense and refrain from writing about anything that has to do, for example, with physical descriptions.”

Former president Donald Trump, talks to members of the media while visiting a bodega, Tuesday, April 16, 2024, who’s owner was attacked last year in New York. (AP Photo/Yuki Iwamura)

He said “there was really no need” for the media to mention one widely-reported tidbit that a juror speaks with an Irish accent.

Anonymous juries have long existed, particularly in terrorism and mob-related cases or when there is a history of jury tampering. They have been ordered more frequently in the last two decades with the rising influence of social media and the anonymous hate speech that is sometimes associated with it. Usually courtroom artists are told they aren’t permitted to draw the face of any juror in their sketches; New York courts do not permit video coverage of trials.

During the Trump defamation trial in Manhattan federal court earlier this year, jurors had heightened protection of their identities by a security-conscious judge who routinely did not allow anyone in his courtroom to have a cellphone, even if it was shut off. Jurors were driven to and from the courthouse by the U.S. Marshals Service and were sequestered from the public during trial breaks.

When asked general questions about themselves during jury selection in that case, prospective jurors often gave vague answers that would have made it nearly impossible to determine much about them.

After the ruling in that case, Judge Lewis A. Kaplan ordered the anonymous jury not to disclose the identities of any of the people they served with, and advised jurors not to disclose their service. So far, none have come forward publicly.

Kuby said the ability of lawyers at Trump’s trial to research the backgrounds of jurors was important.

“Both sides have interest in preventing sleeper jurors who have their own agenda from serving on the jury,” he said.

Neama Rahmani, a former federal prosecutor who is president of the West Coast Trial Lawyers, said the difficulty at the Trump trial is weeding out people with extreme viewpoints.

“Everyone in the entire country knows who Donald Trump is,” Rahmani said. “Some think he’s a criminal traitor and insurrectionist. Others think he’s a hero. You don’t have a lot of people in the middle.”

Associated Press writers Michael R. Sisak and Jake Offenhartz contributed to this report.

What Suicide Data for Public Safety Officers Tell Us

Police officers are at a greater risk of dying by suicide than the general public, and even more likely to die by suicide than in the line of duty, according to evidence from prior research. But many fundamental questions have remained unanswered for lack of comprehensive data: who, where, how, in what roles, and in what circumstances are public safety personnel dying by suicide?

CNA has begun to address those questions, recently publishing the first examination of a systematic, national, and comprehensive effort to collect data on the extent of public safety deaths by suicide. This new research brief is an analysis of a database compiled by First H.E.L.P. , an organization that voluntarily collects data on suicides of law enforcement, correctional officers, firefighters, emergency medical personnel, and 911 telecommunicators. Our report focuses specifically on law enforcement and corrections personnel, examining the 1,287 deaths by suicide that were recorded from 2016 to 2022.

Suicide Data Findings

Among many other findings, the analysis found that annual public safety personnel deaths by suicide rose from 152 in 2016 to a peak of 234 recorded deaths in 2019 before declining during the pandemic. The number of deaths climbed again in 2022. It is possible that some of these changes are affected by data availability. As families, friends, and colleagues become increasingly willing to confront the stigma surrounding suicide and mental health, they may have become more inclined to provide the kind of voluntary data First H.E.L.P. collects. First H.E.L.P. has also suggested that the pandemic may have provided public safety personnel with a renewed sense of purpose, potentially reducing the incidence of suicide in 2020 and 2021.

Source: CNA analysis of First H.E.L.P. data.

Another important finding showed that 60 percent of officers who died by suicide were known to be experiencing some life challenges. The most prevalent of these challenges was depression, affecting 34 percent of those officers who died by suicide. It was followed by post-traumatic stress disorder, or PTSD, reported among 27 percent of officers. Taken together, mental health issues emerged as the category of life challenge affecting the highest proportion of public safety personnel, with 46 percent experiencing depression, PTSD, another mental illness, childhood trauma, or grief from the recent loss of a loved one. The second highest category was work-related challenges, encountered by 25 percent of these individuals. Another recent CNA report examining the work and life stressors among public safety personnel identified the most prominent stressors to be work/life balance, lack of support, being overworked and experiencing burnout, and challenges with colleagues.

Despite the majority of this group experiencing adversity, only 23 percent were reported to be seeking any kind of help. Approximately 17 percent of officers sought assistance for PTSD, and 7 percent sought any form of mental health treatment. CNA has previously explored deterrents to seeking mental health support, including concerns related to confidentiality, cultural competency, and stigma.

The data also indicate that White individuals account for 80 percent of deaths by suicide in this population, though they make up 69 percent of the public safety workforce. This is not entirely surprising. Studies of the broader U.S. population have found that Black individuals often exhibit lower rates of depression and anxiety than their White counterparts, despite facing greater exposure to stressors that typically undermine mental well-being.

We found that firearms were used in 82 percent of public safety personnel deaths by suicide. Since public safety personnel have greater access to firearms as a result of their profession, they must be afforded stronger protections against their unsafe use, including secure firearm storage. These are just a sampling of the findings contained in our report.

The Law Enforcement Suicide Data Collection Act

The insights afforded by analysis of First H.E.L.P. data hint at the necessity of a truly national dataset on suicides of public safety personnel. In 2020, Congress enacted the Law Enforcement Suicide Data Collection Act, which tasks the FBI with collecting national data on suicides. However, the FBI collects these data directly from law enforcement agencies, with limited success so far. The FBI reports 50 suicides for 2022 , submitted by just 39 law enforcement agencies nationwide. In contrast, First H.E.L.P. data reported 183 deaths by suicide using submissions from friends, family members, or acquaintances, as well as Google Alerts and social media. The work by the FBI is in its early stages, and it's essential to recognize and address any shortcomings in the existing data collection processes. There is a pressing need for further refinement and expansion of federal data collection methodologies to achieve a more comprehensive understanding of this critical issue on a national level.

The prevalence of deaths by suicide among public safety personnel is a public health crisis that affects the safety of all. Not only should we ensure the well-being of public safety personnel for humanitarian reasons, but the current level of stress experienced by public safety personnel is unsustainable—as indicated by waning national staffing levels . CNA analysts work with public safety agencies across the country to improve agency member well-being , and recently partnered with command staff of several public safety organizations to provide a webinar on organizational stress . This webinar provided an opportunity for peer learning about supervisory stress and the importance of the command staff in reducing organizational stressors for their supervisees. Continuing to address these work-related stressors is critical, as each death by suicide in the public safety community is already one too many.

Jessica Dockstader is an expert in officer wellness and Daniel Lawrence is a specialist in law enforcement research with CNA’s Center for Justice Research and Innovation . Special thanks to Karen Solomon, Joe Willis, Lew Solomon, and First H.E.L.P. for collecting and providing these data and collaborating with CNA on the analysis.

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