research design example about social media

Social media research: Step-by-step tutorial with examples

• Introduction: What is social media research?
• Step 1: Develop a research design
• Step 2: Collect & import your social media data
• Step 3: Data preparation

Step 4: Get an overview

• Step 5: Categorize your data
• Step 6: Aggregate & present your results

Further learning materials

Friday, January 5, 2024

How to conduct social media research with MAXQDA?

Social Media has drastically changed the way we communicate. Nowadays it’s a lot easier for an individual to communicate with a large audience or with strangers living on the other side of the planet, and to find and communicate with others researching similar topics. Companies, organizations, and political parties can target a specific group of people for their campaign and receive immediate feedback. So, it’s not a surprise that online communication has become more prevalent, which in turn has increased the significance of social media platforms.

Researchers and marketers alike benefit from the wealth of data available on social media platforms, gaining insights into the public’s opinions, communication patterns, and more. Social media research describes the process of collecting and analyzing social media data, such as posts, comments, and likes in order to understand communication patterns, public opinions, and trends.

Who conducts social media research?

Compared to other data collection instruments, such as focus group discussions, collecting social media data is less resource-intensive as the data is easily accessible. However, researchers are confronted with extensive data when performing social media research. Depending on the topic thousands and thousands of posts and comments exist. Consequently, social media researchers need QDA software that is well-equipped for challenges like these, such as MAXQDA. MAXQDA can facilitate your social media research with its numerous data organization and analysis tools. MAXQDA’s auto-coding and sentiment analysis are particularly useful tools, allowing you to explore many posts without reading each one individually. Furthermore, AI Assist, MAXQDA’s AI-based features, are well-suited to handle big data. In the present guide we aim to explain how you can perform social media research with MAXQDA.

Step 1: Develop a research design for social media research

As for any other research project, we advise you to develop a research design before starting your social media research. A research design serves as a structured plan outlining how a researcher intends to answer a specific research question. Determine the specific social media data you wish to analyze and define the precise methodology for your analysis. Among other considerations, ask yourself which social media platform(s) you want to consider, whether there is a time frame of interest; and if you plan to exclusively focus on social media posts containing particular hashtags or keywords. You must address these questions to develop a well-designed study that ensures reliable and valid results. We recommend reading our Research Design guide if you need clarification on what a research design entails.

Please note that the order of the steps presented here is flexible and depends on your research design and research question.

Step 2: Collect & import your social media data

With MAXQDA, you have several options for importing your social media data. On the one side, MAXQDA provides specialized import tools for YouTube comments and specialized analysis tools for YouTube data and X (formerly known as Twitter) data. Suppose you want to import and analyze data from a different social media platform. Then, you can either use MAXQDA’s WebCollector to collect and import entire webpages into MAXQDA or another social media data collection service, saving the data in a MAXQDA-compatible format, like an Excel file. There are several online tools for exporting social media data.

MAXQDA’s WebCollector

You can use MAXQDA’s WebCollector – a free Chrome Browser extension – to export entire websites in a format that can be imported into MAXQDA. The free MAXQDA WebCollector is availale on the Chrome WebStore.

Get the MAXQDA WebCollector

After installing the extension, export the webpage from your social media platform of interest. In the case of X (formerly known as Twitter) you have two options. You can either export only top-level posts or a specific top-level post, including all its replies. Search for a hashtag and export the search results, i.e., all posts containing this hashtag, by opening the WebCollector extension and clicking “Collect.” If you want, you can add notes in the Document Memo section, such as the time frame or other parameters of your search. Upon import into MAXQDA, these notes will be imported as a Document Memo.

Use the MAXQDA WebCollector to export social media data

In the case you are specifically interested in specific posts, e.g., posts from a certain account or posts with a lot of replies, click on the post so that the original post and all comments are displayed. Now, export the website with MAXQDA’s WebCollector to compile the original posts, including all replies.

Step 3: Social media research data preparation

Before starting the actual analysis, you might want to clean and organize your data in a meaningful way. For example, you could remove irrelevant and duplicate posts. You could also organize your data in document groups, e.g., based on the social media platform, a time range, a hashtag, or whatever category is important to your social media research.

Organize your data in Document groups

You may add variables to the imported social media data depending on your research design. For example, when investigating social media trends over time, it can be handy for further analysis to add variables such as the date and timing of the post. To do so, simply go to the “Variables” tab and click “List of Document Variables.” By clicking “New variable,” you can add new variables, specify their type, and define missing values.

Add document variables to improve your social media research

Depending on your research approach, you might benefit from an overview of the data before creating and applying codes, e.g., when following an inductive approach. In other cases, you might already have codes in mind and use them prior to summarizing the data, e.g., in deductive approaches.

When following an inductive approach, you might want to get a basic understanding of the collected social media data and base your codes on the actual content. MAXQDA offers numerous tools, allowing you to get a quick overview. Especially useful when working with big data, such as in social media research, are MAXQDA’s auto-coding and AI-based tools.

Summarize social media data with AI Assist

We acknowledge that AI can assist researchers in qualitative data analysis as well as in other areas of life. Therefore, we developed the AI Assist add-on – your virtual research assistant. AI Assist features several tools that can facilitate your social media research. AI Assist’s Summarize Document function is handy for a quick content overview. This feature creates a summary of entire documents, e.g., of a post and its replies, which it stores in Document Memos. To let AI Assist summarize your document, right-click on it in the Documents window, and choose AI Assist > Summarize Document. You can edit and refine the summary within the Document Memo. These summaries might help you get an idea about the key points discussed and develop codes accordingly.

With AI-generated summaries you can speed up your social media research

Automatically analyze the public’s sentiment

Often, people performing social media research are not interested in every single opinion of every single individual but in the general sentiment towards a topic, politician, issue, or product. With MAXQDA, you can perform a sentiment analysis in no time. To perform a sentiment analysis, open the Smart Coding Tool in the Codes tab. Since the Smart Coding tool works on the level of coded segments, you need to dummy-code your data prior to the sentiment analysis. When importing YouTube comments, comments and replies are automatically coded. However, when importing data through other means, such as via the WebCollector, you may want to manually create the codes ‘post’ and ‘reply’ to quickly code your data. Subsequently, you can perform automatic sentiment analysis by clicking on the button “Analyze Sentiments.” To autocode your social media data with the respective sentiment, click “Autocode Segments with Sentiment.” Then, MAXQDA creates the code ‘Sentiment’ with the identified sentiments as subcodes. By looking at the code frequencies you get a first impression of the general public sentiment.

Autocode the sentiment of your social media data

Subsequently, you can use MAXQDA’s retrieval function to, e.g., focus your social media research on negative posts. To do so, simply activate the documents of interest and the code ‘Sentiment’ > ‘Negative’. All text segments coded with this code will be displayed in the Retrieved Segments window. If you plan to create subcodes, for example to divide the negative sentiment into reasons why people dislike your product, you can again use the Smart Coding tool. Select the code ‘Negative’ from the Code tree on the left site and MAXQDA will display only the segments with a negative sentiment to which you can apply additional codes.

Summarize coded segments with AI Assist

Rather than going through the ‘Negative’ posts individually, you can again use the power of artificial intelligence to create a summary of the coded segments. To do so, right-click the code ‘Negative’ in the Codes window and select AI Assist > Summarize coded segments. Similarly, to the Summarize Document feature, AI Assist will add the summary in a memo.

Step 5: Categorize your social media research data

In many qualitative research projects, including social media research, coding/categorizing your data is an important step. When working inductively, the AI-generated summaries might provide initial ideas for codes. When working deductively, you probably already have codes in mind. With MAXQDA you can easily create codes, assign code colors, and define rules for coding in the New Code window regardless of your approach. Furthermore, you can organize your codes hierarchically. But there is more – MAXQDA allows you to create emoticodes which might come handy when analyzing social media data. For more information on various coding methods, you can refer to:

Learn more about coding with MAXQDA

Autocode your social media data

Especially useful for big data is MAXQDA’s Text Search & Autocode feature, which is located in the Analysis tab. This feature allows you to search for keywords and automatically code them. You can also use logical operators, such as OR, to search for a list of keywords simultaneously e.g., to find all synonyms of a word with just one search. If you are interested in certain concepts, you can create dictionaries of keywords defining the concept and search for multiple concepts at once (search for the whole dictionary). To do so, you first need to create a dictionary. Therefore, go to the MAXDictio tab and select Dictionaries.

Search & autocode important keywords for your social media research

Generate subcode suggestions with AI Assist

In the coding of qualitative data, researchers often start with broad codes, intending to refine them in a later step of the social media research. Alongside the Smart Coding Tool, which is ideal for code refinement, as explained earlier, AI Assist’s “Suggest Subcodes” is another valuable tool. You can use this feature to to get subcode suggestions. Simply, right-click on a code and select AI Assist > Subcode Suggestions.

Step 6: Aggregate & present your results

A crucial step involves consolidating your social media research results into a format that is easily understandable for others. For example, charts and visualisations can aggregate huge amount of data in an easily comprehensible graph that answers your research question. Of course, MAXQDA has integrated visualisation and charting tools. Some tools that might be especially useful for presenting social media data are presented in the following sections.

Word Cloud for visualizing the most frequent words

MAXQDA’s World Cloud, which can also be used with data that hasn’t been coded, is one of the most appropriate visualization tools in social media research. Select the document(s) that serve as the basis for your word cloud and generate a visual representation of the most recurring words. To exclude frequent, yet non-informative words such as ‘the’ or ‘a,’ you can apply a stop word list to the data, effectively filtering out these ubiquitous terms. We offer several Stop Word Lists in several languages on our website, so you don’t have to create one yourself.

Get Stop Word Lists

Word Cloud displaying the most frequent words of YouTube comments

Visualize trends

If your social media research analyzes a topic over time, the Trends function might also interest you. Currently, MAXQDA offers Word Trends, Code Trends, and Dictionary Categories Trends. To explore how code or word frequencies change across time, you should store your social media data in distinct documents – one document per time range. While Word Trends can be used even when the data is not coded, Code Trends requires coded data. No matter whether you are using Code or Word trends, select Trends for multiple documents. Then, select the documents (and codes) of interest and MAXQDA will visualize them. For example, you can use the Code Trends tool on auto-generated sentiment codes to investigate how sentiments towards a topic change over time.

Aside from analyzing trends across time, you can also use MAXQDA’s Trends tool to compare reactions, e.g., between different social media plattforms. To do this, you need to organize your data as follows: create a separate document for each social media plattform containing all posts of interest. Next, choose your preferred Trends tool and again choose trends for multiple documents. In case you are interested in how a discussion evolves in a comment section, given that the data is stored in one document, you can opt for the single document trends feature. MAXQDA splits the document in 10 segments, allowing you to see how word/code frequencies look across them.

Visualizing sentiment trends for #maxqda across weeks

Write your report with QTT

Questions-Themes-Theories (QTT) provides an innovative workspace for gathering important visualizations, notes, segments, and other analytical results. It is an excellent tool for organizing your thoughts and crafting your social media research report. To get started, create a dedicated worksheet for your topics and research questions, and populate it with pertinent analysis elements extracted from other MAXQDA functions. For example, you can incorporate your Trends visualization to a QTT worksheet by clicking on the button, as shown in the screenshot below. Exploratory coded segments related to a set of social media posts can be added to the QTT worksheet via the context menu. For each imported element you can add insights. Furthermore, you have the option to add your conclusions and theories, as well as your research design. Subsequently, you can view all analysis elements and insights to write your final conclusion. The new Questions-Themes-Theories tool is designed to assist you finalize your social media research. With just one click, you can export your worksheet and use it as a starting point for your social media research report.

Add a visualization to a QTT worksheet

We offer a variety of complimentary learning materials to help you get started with your social media research. Check out the recording of a spotlight session on analyzing social media data with MAXQDA which was held at the MAXDAYS conference in 2023. In addition, the free book “The Practice of Qualitative Data Analysis,” provides ten case studies with brief real-world examples, demonstrating MAXQDA’s practical applications.

Spotlight Session: Analyzing Social Media Data with MAXQDA

The Practice of Qualitative Data Analysis

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Research Design Review

A discussion of qualitative & quantitative research design, social media in research design.

It is difficult to escape the onslaught of attention that has been given to social media in the context of research design.  It is almost impossible to pick up a trade publication and not be struck by the breadth and near-frenzy of discussion among researchers concerning social media.  For many, Facebook, Twitter, online communities and the like are virtual fountains overflowing with consumer content just waiting for researchers with their buckets to scoop up every juicy detail.  As someone recently put it, “[Social media] provides a gold mine of information just a click away.” 

These researchers are eager to promote and defend social media as worthy components of research design.  The argument goes that social media revolutionizes the research process by enabling fast and cheap access to “data” while bringing creativity and fun to an otherwise too-serious discipline.  This argument extends not only to information gathering but to analysis as well, i.e., digging around in social media results in lots and lots of text making it ideal for computer-based content analysis.

But is a social-media-centric approach good research?  Social media is certainly a valid and potentially important tool in exploratory or secondary research efforts – and, indeed, marketers owe it to themselves to regularly search Twitter for the latest chatter concerning the company and its products/services.  And online communities clearly offer a significant vehicle for researchers to immerse themselves in the end-user experience.  But the idea that Twitter “provides highly reliable” information (as one researcher recently asserted) is, from a research perspective, pure nonsense.  And the idea that lurking on Facebook or Twitter can or should replace researcher-respondent interviewing (as some have suggested) ignores the essence of what it means to conduct “research” and to be a “researcher.”

This discussion is not about traditional vs. new research methods – the idea that traditional qualitative and quantitative research designs are stale and inappropriate in this modern, overtly-social culture – or even about qualitative vs. quantitative.  It is simply about basic research principles that never become outmoded.  The enthusiasm towards the potential of social networking sites in the design of primary research snubs certain fundamental design considerations, not the least of which is transparency.  Transparency is only achieved to the degree to which the researcher can account for the variability impacting results and state with some confidence the attitudes and behavior among research participants based on a knowledge of their framework within the sphere of interest.  This principal (transparency) alone is enough to discourage any serious thoughts of Facebook or Twitter as viable primary research design tools.

Public information and content has been around us everywhere for a long time – letters to the editor in print media, callers to call-in radio or television shows – and researchers have always had the opportunity to utilize these resources.  But good research design is not about eavesdropping.  It is not about grabbing comments and ideas wherever they can be found from the most extroverted segments of society then throwing them together and calling it insight.

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Adolescent Social Media Use and Well-Being: A Systematic Review and Thematic Meta-synthesis

• Systematic Review
• Published: 17 April 2021
• Volume 6 , pages 471–492, ( 2021 )

Cite this article

• Michael Shankleman   ORCID: orcid.org/0000-0002-7150-8827 1 ,
• Linda Hammond 1 &
• Fergal W. Jones   ORCID: orcid.org/0000-0001-9459-6631 1  

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19 Citations

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Qualitative research into adolescents’ experiences of social media use and well-being has the potential to offer rich, nuanced insights, but has yet to be systematically reviewed. The current systematic review identified 19 qualitative studies in which adolescents shared their views and experiences of social media and well-being. A critical appraisal showed that overall study quality was considered relatively high and represented geographically diverse voices across a broad adolescent age range. A thematic meta-synthesis revealed four themes relating to well-being: connections, identity, learning, and emotions. These findings demonstrated the numerous sources of pressures and concerns that adolescents experience, providing important contextual information. The themes appeared related to key developmental processes, namely attachment, identity, attention, and emotional regulation, that provided theoretical links between social media use and well-being. Taken together, the findings suggest that well-being and social media are related by a multifaceted interplay of factors. Suggestions are made that may enhance future research and inform developmentally appropriate social media guidance.

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Acknowlegement

We extend our gratitude to the authors of the original studies for bringing forth the perspectives of young people.

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The review protocol including review question, search strategy, inclusion criteria data extraction, quality assessment, data synthesis was preregistered and is accessible at: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=156922 .

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Shankleman, M., Hammond, L. & Jones, F.W. Adolescent Social Media Use and Well-Being: A Systematic Review and Thematic Meta-synthesis. Adolescent Res Rev 6 , 471–492 (2021). https://doi.org/10.1007/s40894-021-00154-5

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DOI : https://doi.org/10.1007/s40894-021-00154-5

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The Problem With Using Social Media as a Design Education

By Mel Studach

This is an edition of The Source newsletter, AD PRO’s essential read for design industry professionals. Sign up here to get it delivered to your inbox .

Twenty-five days were left on Shawn Henderson’s countdown to the Kips Bay Decorator Show House opening when I caught up with AD100 designer . At that point, his north-facing bedroom on the home’s fourth floor was all but a rosy pink rendering—with its share of accompanying showcase headaches. Crunchtime in session, he was still more than willing to offer real talk for fellow designers considering their first show house, air qualms with today’s design monotony, and underscore the importance of a design education. Enjoy the read—and check out Shawn’s dashing bedroom, now on view on New York’s Upper East Side.

Mel: This is your second go at the Kips Bay Decorator Show House in New York. Have your past learnings come in handy this time around?

Shawn: The last time I did the Kips Bay Decorator Show House was back in 2012, and at the beginning of this year, I had been feeling like it might be time for me to do it again. When [design co-chair Alexa Hampton] emailed me to participate, I was like, OK, it’s a sign. They assigned me a bedroom, and it's going well—but these things are a moving target, right? Decisions are made and changed constantly based on availability and quantities. It’s all hands on deck up until the minute we’re installing. There's a lot of energy going into this one little room!

What was motivating you to want to participate this year?

I think it's the best show house in the country, and it's a real honor to be included in it. It’s also a great opportunity for press coverage, and after having published my book in 2021, I felt like it was a way for me to show something that highlighted my evolution in design right now—where I am in my career and in my life. For me, that’s embracing more color. It’s keeping things fresh and current and pushing the envelope.

Shawn Henderson's “Steel Sanctuary” bedroom in the 2024 Kips Bay Decorator Show House New York .

What advice do you have for designers preparing for their first show house experience?

It is not for the faint of heart! You have to realize what an opportunity it is to present a space that you've created to the masses. You should really push it as far as you can go in terms of what you’re trying to create, and make sure that it’s visually appealing and different and exciting. But it should be within reason—it can be exciting and beautiful without being too editorial.

Outside of show house stressors, what’s been bothering you as of late?

I’ve been saying this for the past couple of years, but I feel like it’s more important than ever for people to apprentice and to put their time in and to learn this craft before launching out on their own and just, you know, deciding to become a decorator. It’s a real disservice to our industry when there is this lack of experience.

Listen, clients are tricky. And there are no real industry standards for us. I work in a certain way, and I’ve learned this from people whom I have worked for in my past. When people don’t have that base of knowledge and experience from the business point of view, it discredits how we practice as a business.

Why do you think this issue is more prevalent now?

Social media. It has been a great tool for all of us—and I don’t want to begrudge anybody making money and doing their thing—but it’s important that people are still putting good design out there in the world. It doesn't have to be my taste, but we’re seeing so much of the same thing over and over right now. People see that trending design and then it gets copied and spread out, and it's just not exciting.

Participating in this year's show house was about sharing “where I am in my career and in my life," says Henderson. "For me, that’s embracing more color.”

In your call for more education, what wins: design school or apprenticeship—or both?

I talk to a lot of people—whether they’re just starting out, or people who want a change of career—and I think no matter what, some level of schooling is important. There are skills you need to learn—the real basics, like AutoCAD or how to sketch. And while you’re doing that, work and learn from a mentor. That is the most valuable experience you could ever get.

Totally. We had Nicole Hollis on a recent business panel , and she was saying how essential apprenticeship is for observing client relations and learning how to navigate tough conversations.

Absolutely. Good communication skills are essential both within the firm and in dealing with the managing clients. It’s all about managing expectations.

How do you approach those tough conversations?

It’s never fun, but you have to stand up for yourself. This is what I tell myself: This is a business that I'm running, and it needs to be treated as such. I'm showing up for myself, and there's nothing wrong with that. You have to take the emotion out of it, and leave it at that. Period, the end.

This interview has been condensed and edited for brevity and clarity.

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