does use of social media impact academic performance essay

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How Does Social Media Use Affect Academic Performance?

You’re at your desk with a fresh cup of coffee, ready to get cracking on the long–and fascinating, as your teacher put it–physics worksheet. Oh, and it’s due bright and early the next day—you’ve got a long night ahead. But then your phone lights up, and the notifications roll in. You could put the phone away until you finish (you told yourself you would!), but how much harm is a few minutes?

Forty-five minutes later, you’re deep into figuring out how your horoscope corresponds with every Snapchat friend. 

Welcome to the age of social media. 

Likely, you’ve learned, to some extent, about how social media can impact mental health, focus, wellbeing, quality of life, sleep, etc. Perhaps you’ve taken it in but thought,  I’ll be fine . Most of us tend to engage in this type of thinking from time to time, where believe ourselves to be the outlier. This is textbook self-exceptionalism . As humans, we often consider ourselves to be kinder, more rational, and/or smarter than most others.

Well, other than the handful of super-humans out there–Usain Bolt qualifies?–most of us aren’t. But this is great news! It means we’re all in the same boat. And that means, to put it simply, that we’re all susceptible to social media’s consequences. 

Social media has addictive properties

Understanding–scientifically–how social media really works is a great way to recognize how you can develop healthier media habits. The reality is, social media has the potential to suck you in and turn you a into chronic consumer. In fact, over several years, researchers have found that social media may have addictive properties similar to drugs.

Social media basically acts like a PEZ dispenser, except instead of feeding sugar, it feeds dopamine. Just like with sugar, once you get it, you want more. And when you don’t have it, you may go through a “crash,” or withdrawal. 

And this addiction, as it seems, can affect academic performance.

A 2019 study  on the relationship between social networking addiction and academic performance found that students who were addicted to social networking had significantly lower academic performance than students who were not addicted to networking. 

Similarly, findings from a 2015 study demonstrated that both the amount of time spent on social media and the extent to which one is addicted have negative impacts on academic performance. 

Although we have the ability to turn off notifications or the device, social pressure still persists. No one likes feeling out of the loop. Plus, we love to be a part of something, which social media provides—eternal community.

And you can’t ignore the bandwagon effect, how we tend to strive to conform to what everyone else is doing in social situations. This is particularly prevalent for young students, who are particularly influenceable. Research  shows that most people change their perception to conform with the rest of the group–and that this effect is stronger for younger people. 

Luckily, just like sugar, if you slowly and consistently change your media habits, over time, dependency (or even addiction) will weaken.

Social media use and academic performance are significantly related

Science Daily conducted a meta analysis of several studies focusing on how social media impacts on academic performance, finding that: 

• Students who regularly use Instagram while studying tend to perform slightly worse than students who don’t use social media while studying. 
• Students who often log into social media and spend lots of time using it slightly lower grades than those who aren’t avid social media users. 

Evidently, balancing social media usage with studying or doing homework can yield consequences in students’ academics. But really, this isn’t so surprising. Time and time again, research has shown that humans aren’t good at multitasking, although we often assume otherwise!  

In a study from 2021 , researchers looked at the effects of social media among university students, finding that out of 300 students, 97% engaged in social media, with only 1% using it for educational reasons. Additionally, 57% of them were addicted! This provides a glimpse at not only the sheer volume of social media consumption, but its powerful effects. 

Social media affects sleep and, in turn, academic performance

It’s impossible to avoid the fact that as social media prevalence has increased, we’ve changed–we’ve become a high-paced, high-stress society. We’re always on the go. 

Additionally, we always have access to communication, which, yes, has tons of benefits. For instance, we are blessed with long distance communication, emergency phone calls, large-scale team meetings, among other positives.

But at the same time, we’re getting burnt out , because “downtime” for many people is never truly downtime. And also, a key contributor to burnout is that  it’s difficult to get that high-quality sleep need with all that screen time. 

Research shows that there is a direct link between social media usage and sleep deprivation. For many, it’s the norm to engage in social media before bed. And while it can seem like a calming, low-stress activity to do before bed, it can be harmful in several ways. 

First, social media is distracting and can often push bedtime back. Second, the blue-screen light can have negative affects on your sleep quality. Sleep Health Journal found that exposure to blue screens in the evening can cause morning grogginess, daytime dysfunction, and decreased sleep quality. 

And I’m sure you can guess how this further weakens academic performance. Students can easily develop a cycle where they engage in extreme social media usage, have poor quality sleep, and then have lower academic performance.

So if you’re trying to turn over a new leaf by becoming a morning person , it’s time to curb your before-bed scrolling.

It’s not all bad news!

While this can seem dreary and daunting, it’s not all bad. Science Daily’s meta-analysis (mentioned above) points to a silver lining.

The research showed that:

• Those who use social media to communicate about academic/school-related topics tend to have marginally better grades than those who use social media for non academic-related matters.
• Students who are especially active on social media don’t spend less time studying.

So, these results tell us what?

Well, first of all, social media is not innately harmful! The first finding says just that–these students were using social media “intensively,” and didn’t spend any less time studying than non-active users. So from that, we can see that:

a) social media isn’t simply bad for students,

b) it won’t necessarily affect their work ethic, and

c) when used for school-related issues, it usually isn’t harmful. 

The second finding is key to understanding how to moderate social media use. Clearly, even when students spend a lot of time on social media, they still can find the time to study. So, if you exercise self-control to allocate your time to studying when you need to study, and reserve using social media for other times, you can still excel academically.

How can social media improve academic performance?

Evidently, there’s potential danger in the rise of social media, but there’s also overlooked student benefits. Furthermore, during this weird time where lots of students are still learning remotely , understanding how to use social media to your advantage is important. 

A 2020 empirical study that examined how social media may regulate collaborative learning provides us with some useful takeaways. 

First, the researchers found that collaborative learning through social media leads to high levels of student interaction. This includes sharing knowledge and ideas, which may be through forums and discussion posts. Additionally, the researchers found that conversations with teachers through social media lead to a high degree of student engagement.    

Generally, there was a significant, positive relationship between online knowledge sharing and student engagement. And notably, the study highlighted that student engagement is positively correlated with academic performance.

From this, it’s important to recognize that collaborative learning on social mediums is linked to student engagement—which is linked to higher academic performance. So, indirectly, social-media-based collaborative work leads to higher academic performance. 

Windsor University provides more information on how social media can be beneficial to students by:

• Improving practical skills through informational videos
• Helping students with research projects through utilizing data and survey results
• Providing students with valid and reliable sources and data that helps them complete assignments and prepare for lessons

Informative learning and moderation is key

Since social media and technology aren’t going anywhere, let’s take in all the facts the science, and take action. You don’t have to starve yourself of social media. Instead, you can practice exercising moderation and learn new ways to craft your schedule. Think about it like this: as a human, you have a deep-seated desire for control. So each time you apply your knowledge and exercising your strength over social media’s persuasive pull, you’re gaining a little power and a little control. 

Long live your agency!

Author: Lydia Schapiro

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ORIGINAL RESEARCH article

Effect of social media overload on college students’ academic performance under the covid-19 quarantine.

• 1 School of Transportation, Fujian University of Technology, Fuzhou, Fujian, China
• 2 Guangdong University of Petrochemical Technology, Maoming, China
• 3 Stamford International University, Bangkok, Thailand
• 4 Zhengzhou Technology and Business University, Zhengzhou, China
• 5 School of Economics and Management, Xiangnan University, Chenzhou, China
• 6 Graduate School of Education, Stamford International University, Bangkok, Thailand

Features and relevant services of online social media have been attracting users during the COVID-19 pandemic. Previous studies have shown that college students tend to use social media more frequently than other groups. However, in being affected by social media overload, the social media use behaviors of many college students have been out of their control in terms of their capabilities or cognition. Based on the stressor–strain–outcome (SSO) model and the theory of compensatory internet use (TCIU), we developed a research model to study the causes of social media overload and its impact on college students’ academic performance during the COVID-19 pandemic. A total of 441 valid responses from college students through questionnaires in China are collected via purposive sampling and used in the data analysis. This study conducts PLS-SEM to analyze collected data, finding that boredom proneness is associated with overload (stress), which has a bearing on social media overload (strain) and the reduction in final performance (outcome). Through illustrating the psychological and behavioral conditions that hinder the academic performance of students, this study provides deeper insights into students’ uncontrollable use of social media. Moreover, with respect to the identified antecedents, this study aims to find solutions to mitigate the impact of social media overload resulting from boredom proneness on the academic performance of college students.

Introduction

The COVID-19 pandemic has dramatically hit the social operation in the world, resulting in a diversity of risks and challenges facing organizations (Cao; Said et al., 2021 ). In 2021, some regions of the Chinese mainland implemented lockdown policies to curb COVID-19. Boredom proneness during the lockdown period caused the improper use of social media, which may have affected the psychological health of individuals, especially those born between the mid-1990s and early 2010s ( Priporas et al., 2017 ). Thus, we took college students under quarantine and lockdown policies as the research samples to discuss whether college students were experiencing overload triggered by boredom proneness during quarantine. Affected by the COVID-19, many university cannot provide suitable studying environment, and even the class suspension, so the overload intention may come about when the psychological health of individuals. Boredom proneness is described as “the lack of interest in and the difficulty in focusing on current activities” ( Mikulas and Vodanovich, 1993 ; Fisher, 1998 ; Kass et al., 2010 ). Opinions given in this study contribute to deepening awareness and understanding of the excessive use of social media among college students ( Bright et al., 2015 ; Li, 2018 ; Salo et al., 2018 ; Turel et al., 2019 ). Most of the existing studies explore how to enhance classroom collaboration using social media and promote the use of social media in a higher education context ( Al-Rahmi et al., 2018 ) but neglect the correlation between boredom proneness, social media overload and the academic performance of students ( Cao and Sun, 2018 ). The ability to develop evidence-based interventions and solutions is compromised as existing research has largely overlooked the connection between boredom, social media use, and social media overload ( Cao and Sun, 2018 ).

The excessive use of social media may result in overload. We define social media overload according to three common dimensions: information overload, communication overload and system feature overload ( Bowker, 2008 ). Seldom has research investigated the antecedents of information, communication, and system feature overloads on social media ( Lee et al., 2016 ). Previous research has mainly concentrated on the negative correlation between students’ use of social media and student engagement ( Junco, 2015 ; Datu et al., 2018 ). For instance, multitasking behaviors provided by social media are correlated with student engagement ( Junco and Cotten, 2012 ; le Roux and Parry, 2017 ) and well-being ( Becker et al., 2013 ). Although the wide use of social media may cause stress for students and thus affect their academic performance ( Cao et al., 2018 ), seldom have studies used theoretical mechanisms to demonstrate how social media affects the academic performance of students. Giunchiglia et al. (2018) confirmed that the duration of usage social media apps negatively affected students’ academic performance. We aim to expand existing studies using the stressor–strain–outcome (SSO) model in combination with the theory of compensatory internet use ( Davis and Luthans, 1980 ) and to further discuss how boredom proneness causes the perception of social media overload (organism) and how the social media overload subsequently results in a reduction in academic performance (outcome).

The daily life of college students has changed enormously due to the outbreak of COVID-19 ( Khanra et al., 2021 ). College students are the major user group of social media, with a use level higher than average ( Maier et al., 2015 ; Turner, 2015 ). The enforcement of lockdown policies on the Chinese mainland gradually led to an issue regarding the use of social media among college students, resulting in a deviation from its original intended use ( Liu et al., 2021 ). Due to their intense usage of and limited external control over their Internet use, extensive free time, and flexible schedules, university students are more disposed than others to develop problematic social media use ( Turel and Qahri-Saremi, 2016 ). In this paper, we investigate the etiology and consequences of social media overload among university students, the phenomenon in which the extensive adoption and use of social media has exposed people to a massive amount of information and communication demands that may require energy and cognitive processing beyond their capabilities ( Lee et al., 2016 ). In addition, since the COVID-19 broke out in 2019, previous literature has failed to consider special context factors and cannot be used to demonstrate the reasons and psychological mechanisms for social media overload appearing in the lockdown period. Different from previous research, we first of all emphasize that the boredom proneness brought about by quarantine policies has led to social media overload among college students. Second, we investigate a situational state during the quarantine period, which has shaped a process stemming from inner feelings, which generates the social media overload and causes the decline in college students’ academic performance. We have found that social media overload results from the interaction of boredom proneness with three dimensions of overload (information overload, communication overload and system feature overload), thus ultimately affecting the academic performance of college students.

Literature review and theory development

Theory of compensatory internet use.

The TCIU is a contemporary theory that has been widely applied in social media as an extension of the uses and gratifications theory ( Elhai et al., 2017 , 2020 ; Tandon et al., 2020 ). The novelty of TCIU lies in its particular focus on psychopathology as a motivator of problematic internet or social media use ( Elhai et al., 2017 ). Information and communication overload can occur when people turn to social media in order to alleviate their boredom. Therefore, information overload and communication overload are conceptualized as strain factors. Strain can lead to various negative outcomes, such as dissatisfaction, emotional exhaustion, fatigue, or even the discontinued negative with academic performance ( Ragu-Nathan et al., 2008 ; Tarafdar et al., 2011 ; Maier et al., 2015 ). As stated by TCIU, individuals may overuse technologies (e.g., social media) to deal with or compensate for social needs that are perceived as lacking ( Wang et al., 2018 ) and negative emotions or stressors related to their living environment ( Wolniewicz et al., 2018 ). On the basis of TCIU, we consider that college students who are experiencing boredom proneness, which is a negative emotion ( Tandon et al., 2021 ), would increase their use of social media to cope with and compensate for it. We hold the same arguments as those of previous studies that individuals are more inclined to deal with perceived negative emotions ( Tandon et al., 2020 ) and unsatisfied requirements ( Wang et al., 2018 ; Wolniewicz et al., 2018 ) through social technologies, such as smart phones and social media. Thus, we consider TCIU an appropriate theory to establish the theoretical framework of our study. However, some scholars assert that TCIU has been focusing on the psychopathology and negative emotions, making it inadequate for providing theoretical support for social media use behaviors ( Wolniewicz et al., 2018 ). As a result, we contend that TCIU is not able to offer a comprehensive outlook for the study of the proposed associations, especially overload. Therefore, we complement TCIU with the SSO model to consider the associations between boredom proneness, overload and fatigue. In this paper, we investigate the etiology and consequences of social media overload among university students, the phenomenon in which the extensive adoption and use of social media has exposed people to a massive amount of information and communication demands that may require energy and cognitive processing beyond their capabilities ( Lee et al., 2016 ).

Our research model has been developed based on TCIU to explain the stress process combined with the SSO model ( Koeske and Koeske, 1993 ). The SSO model developed by Koeske and Koeske (1993) was originally applied in psychology studies to describe the stress process. On the grounds of this framework, stressors exert an influence on users, thus leading to their behavioral outcome. In the SSO model, stressors are defined as environmental stimuli that are, as believed by individuals, stimulating, troublesome or destructive. Common stressors include overload, conflict and intrusion ( Ayyagari et al., 2011 ; Bucher et al., 2013 ; Maier et al., 2015 ). Strain is an individual’s psychological response to stressors and may have a frustrating effect on an individual’s attention, physical condition and emotion ( Cheung and Tang, 2010 ). Studies of strains, such as emotional exhaustion and overload, are very widely conducted in relevant studies ( Choi et al., 2014 ; Zhang et al., 2016 ). In organizations, stressors are the conditions for factors generating stress, and strain is the psychological outcome of stress. Furthermore, stress is a modulator for the effect of perceived stressors on outcome variables ( Lee et al., 2016 ). Prior studies of stress contend that reduced organizational commitment, poor job performance and discontinuity of intention are the outcomes of stress ( Ragu-Nathan et al., 2008 ; Kim et al., 2012 ). In the past, the SSO model was commonly used to study a stress-related situation and its outcomes in the context of technology use ( Ragu-Nathan et al., 2008 ; Ayyagari et al., 2011 ; Dhir et al., 2018 ). For example, Cheung and Tang (2010) investigated how job stressors (including job characteristics and emotional dissonance) affect employees’ subjective health and work outcome ( Choi et al., 2014 ). Studies have shown that social stress related to customers has a positive effect on emotional exhaustion, which, in turn, has a negative effect on customer orientation and the performance of service restoration. These studies mainly discuss job stress in workplaces. As social media has been extensively used among college students, they are more likely to spend a lot of time on social media, resulting in the excessive use of social media related to technology stress and further bringing about negative outcomes ( Pavlou et al., 2007 ; Aladwani and Almarzouq, 2016 ). In the context of COVID-19, the excessive use of social media and the social media overload caused by boredom proneness among college students constitute stressors that affect individuals’ emotions and attitudes (e.g., overload, regret, or discontent) toward social media, and these stressors will further give rise to adverse outcomes such as a decline in academic performance ( Cao and Sun, 2018 ; Dhir et al., 2018 ; Nawaz et al., 2018 ; Yu et al., 2018 ). This is entirely in line with the major purpose of this study, that is, how stress-related factors trigger social media overload and thus a decline in academic performance (outcome). Consequently, we use the SSO model as the theoretical basis to discuss the negative effect of social media overload resulting from boredom proneness on the academic performance of college students.

Boredom proneness and overload

To be sure, social media is able to facilitate friendship development and maintenance, social contact well-being and knowledge exchange among college students, but it may bring about negative outcomes when it is used beyond individuals’ available resources and energy ( Karr-Wisniewski and Lu, 2010 ). In the context of social media, overload is the key factor for such negative outcomes ( Lee et al., 2016 ). The overload derives from the imbalance between the unexpected demands in the context and the limited handling ability of individuals ( Edwards and Cooper, 1990 ).

Overload, as a typical stressor, has been extensively examined in different research fields such as work overload ( Ayyagari et al., 2011 ), connection overload ( LaRose et al., 2014 ) and social overload ( Maier et al., 2012 ), for some people, this has resulted in overload, which refers to a mismatch between environmental requirements and an individual’s ability to cope. The topic of overload has been studied by many scholars, who argue that overload can be divided into information overload, communication overload and system feature overload ( Bowker, 2008 ). Information overload will appear when the information on social media is too much to be handled properly by an individual, especially when the information is presented in an excessively fast and discontinuous manner. Users reported feeling low on energy and unable to concentrate on important tasks after a period of heavy social media use ( Whelan et al., 2013 ). Communication overload refers to when individuals’ communication skills are challenged when too many communication demands are embedded in social media. System feature overload refers to when the features provided on social media exceed the users’ demands ( Thompson et al., 2005 ). To be specific, the younger generations, like college students, are the major participants in social activities on social media ( Kirschner and Karpinski, 2010 ), and have a strong desire for social contact. Since the interpersonal relationship in a social network is always reciprocal, individuals feel that they are obliged to meet the demands of online friends in the form of emotional or material support ( Maier et al., 2012 ). Individuals are likely to become exhausted in the face of an increasing number of social support requests if they are not able to satisfy such requests, and they may also feel uncomfortable regarding their too frequent responses to such social requests, thus leading to a perception of social contact burden ( Maier et al., 2015 ). Once the number of online social requests goes beyond the handling ability of users, a troublesome environmental stimulus will be generated, leading to a series of emotional and behavioral reactions ( Evans et al., 2000 ). This unwholesome state has been proven by experience to be a stressor that exerts a negative influence on one’s personal life ( Maier et al., 2015 ). Similar to the way that boredom proneness has been found to generate stress in social media users ( Whelan et al., 2013 ), we conceptualize boredom proneness as a stressor for the same population. For example, learners must pay attention to learning materials and other activities, such as familiarizing themselves with increasingly complex SNS system features, responding to demanding social support from friends, confronting the distractive advertising, etc. These overloads lead to negative emotional responses such as stress, frustration, and anxiety, which also occur in learning communities. When individuals feel threatened by the physical and psychological strain generated by SNSs, they have to prevent or reduce the adverse outcomes and restore emotional stability, thus threatening the sustainability of SNS’s massive benefits for people. Therefore, we consider information, communication and system feature overloads as stressors and three dimensions of overload related to the overuse of social media.

College students might have sought out other experiences to relieve boredom proneness during the quarantine and lockdown period, even though these experiences might have caused negative impact ( Bench and Lench, 2013 ). Boredom proneness is an undesirable feeling, so the human brain looks for external stimuli to avoid it. Social media provides almost endless experiences, which attract scores of people to pass time and seek out spiritual and emotional stimuli. However, excessive stimuli may be a bad thing. Prior studies of addiction have mentioned that boredom proneness can result in some adverse outcomes, such as social media overload. Social media become a kind of pathological pursuit for users to relieve their boredom proneness, thus resulting in the issue of overload ( Turel et al., 2014 , 2016 , 2019 ). Many prior studies have explained why people overuse social media, and boredom proneness is a significant influencing factor recognized by scholars; seeking out entertainment and killing time are powerful predictive factors for the use of social media platforms ( Quan-Haase and Young, 2010 ; Ku et al., 2013 ). Boredom proneness drives people to seek more stimulating activities in social media ( Bench and Lench, 2013 ; Alter, 2017 ), which then lead to information, communication and system feature overloads.

According to the logic of addiction studies described above, adverse outcomes will bring about information, communication and system feature overloads when people try to relieve their boredom proneness using social media. Thus, we propose the following hypotheses:

H1 : Boredom proneness is positively correlated with information overload. H2 : Boredom proneness is positively correlated with communication overload. H3 : Boredom proneness is positively correlated with system feature overload.

Antecedents of overload

We consider the overload examined in this study as psychological stress, which is an individual psychological state, and the behavioral outcomes that can be affected by cognitive bias ( Brooks and Califf, 2017 ; Mahmud et al., 2017 ; Steelman and Soror, 2017 ). In previous studies, overload has been extensively investigated as a special type of psychological tension caused by overloads ( Ahuja et al., 2007 ; Maier et al., 2015 ). In the social media context, an excessive amount of information and interaction may weaken user activation and make them feel tired ( Maier et al., 2015 ). Exhaustion refers to a state of extreme overload caused by the long-term and excessive consumption of spiritual resources ( Schaufeli, 1995 ; Ravindran et al., 2014 ). Moore (2000) investigate social networking service (SNS) exhaustion, which is a psychological reaction to stressors, as an outcome of social overload in the social networking environment. The investigation showed that workload is the strongest predictive factor of employee overload. In our context, overload refers to the disgust and potentially harmful and unconscious psychological reactions to stress conditions when using social media ( Maier et al., 2015 ). It represents the tiredness arising from social media use.

Information overload will occur if the information accessible to users on social media goes beyond their ability to handle it ( Zhang et al., 2016 ). Specifically, the information overload would have resulted if college students made responses that went beyond their management and handling abilities in order to eliminate boredom proneness during the quarantine and lockdown period. It can produce stress and negative emotions, so people cannot easily cope with requests from social media platforms, which is undesirable ( Cao and Sun, 2018 ). Plenty of information is generated on social media as the number of users and their level of activation increases ( Lee et al., 2016 ). As a result, college students need to be able to cope with the incessant information generated on social media, thus causing overload. The overabundance of information on social media may exceed the expected cognitive range of the human brain, making users feel overwhelmed and tired ( Lee et al., 2016 ). The massive amount of information on social media can quickly go beyond the cognitive range of humans, making people feel at a loss ( Wurman, 1990 ). Previous studies have shown that information overload is one of the major antecedents of social media overload in the social media context ( Lee et al., 2016 ; Zhang et al., 2016 ). Confronted with the massive amount of information, users may feel out of control ( Zhang et al., 2016 ) and may regret using social media ( Cao and Sun, 2018 ; Nawaz et al., 2018 ), thereby leading to social media overload ( Cao and Sun, 2018 ). Therefore, users may feel extremely tired on social media when they perceive information overload ( Gao et al., 2018 ). The overload will be evident when users feel that it is difficult to manage large amounts of information and communication from others ( Lee et al., 2016 ). Based on the above statements, we posit the follow hypothesis:

H4 : Information overload is positively correlated with social media overload.

Social media provides a diversity of features to facilitate communication ( Garrett and Danziger, 2007 ; Ou and Davison, 2011 ). Message and conversation requests from other users attracts the attention of users and excessively interferes with their behaviors, resulting in communication overload ( Karr-Wisniewski and Lu, 2010 ; Cao and Sun, 2018 ). As reported by Lee et al. (2016) , communication overload is a source of overload in the context of social media use. Users will perceive a communication overload if there are too many social requests to cope with and be satisfied on social media ( Karr-Wisniewski and Lu, 2010 ). After coping with the communication requests, individuals need take several minutes to recover the interrupted work or learning ( Karr-Wisniewski and Lu, 2010 ; Ou and Davison, 2011 ). Communication overload may repeatedly interrupt the daily learning tasks of college students ( McFarlane and Latorella, 2002 ; Cho et al., 2011 ), making them feel tired and giving rise to more severe spiritual or physical diseases ( Deutsch, 1961 ; Klapp, 1986 ). We, therefore, contend that college students often feel overload due to communication overload.

We develop the following hypothesis:

H5 : Communication overload has a positive impact on social media overload.

System feature overload will appear if the features of applications are not suitable for current tasks or the system features are too complex to complete tasks ( Thompson et al., 2005 ; Karr-Wisniewski and Lu, 2010 ; Zhang et al., 2016 ). In the social media context, system feature overload refers to social medial users’ perception of technology features. It can also be defined as a perception that features provided by social media exceed user demand ( Thompson et al., 2005 ; Zhang et al., 2016 ). If system features on social media often change and are too complex for users, system feature overload will appear and result in adverse outcomes, such as social media overload. For example, Facebook updates its system features and user interface almost once a week ( Fu et al., 2020 ), so users need to spend more time and attention to adapt to these frequent changes. System feature overload is particularly obvious when the design changes do not match user habits ( Ayyagari et al., 2011 ), especially when users have become accustomed to an appearance and find the system changes overwhelming. Users may also experience system feature overload, thus leading to the perception of social media overload ( Lee et al., 2016 ). Frequent unnecessary updates for feature interfaces will lead to social media overload ( Ayyagari et al., 2011 ; Ravindran et al., 2014 ). Hence, we contend that college students may be tired of social media use and feel overloaded when they realize that the cost required to learn and use system features on social media outweighs their benefits.

Based on the above statements, we make the following hypothesis:

H6 : System feature overload has a positive impact on social media overload.

Relationship between overload and academic performance

Indeed, the most popular social media applications are designed to encourage compulsive use ( Alter, 2017 ). Many people are unable to override their impulsive habitual use of social media ( Turel and Qahri-Saremi, 2016 ) and smartphones ( Soror et al., 2015 ). Social media users often do not get all the functionality they want from one platform and need to constantly switch between too many different (non-) technological alternatives, resulting in negative perceptions which Maier et al. (2015) . The relationship between social media use and academic performance has been a hot topic in the education field in recent years ( Liu et al., 2017 ). Meta-analysis has shown that the excessive use of social networking services has a significantly negative association with academic performance ( Aladwani and Almarzouq, 2016 ). It has also found that the compulsive use of social media leads to problematic learning outcomes. As a result, we consider the academic performance of students as an outcome in this study.

Overload is a complex physical and psychological state. Physical overload is clinically defined as “not [being] able to maintain the required or expected strength” ( González-Izal et al., 2012 ). Psychological overload is described as a state of overload that is related to stress and other intensive emotional experience ( Shen et al., 2006 ). Overload is a kind of subjective inner feeling that varies from person to person ( Nail and Winningham, 1995 ). Physical overload is more likely to appear in the mandatory environment related to physical labor but not in the context of social media use, so social media overload can be regarded as a form of psychological overload ( Zhang et al., 2016 ). Overload brings about a variety of outcomes that decrease students’ academic performance ( Junco, 2015 ). Academic performance means the extent to which students achieve their short-term or long-term educational goals. Prior studies have discussed all sorts of negative outcomes caused by social media use ( Tarafdar et al., 2015 ), and reduced academic performance is the most common one. Past studies seldom demonstrate that social media overload can lead to reduced academic performance among college students ( Ayyagari et al., 2011 ).

We contend that social media overload derives from individuals’ dependence on social media, particularly from college students’ excessive use of social media to eliminate boredom proneness during the COVID-19 lockdowns. This has been identified in recent research findings. For example, Islam et al. (2020) found that the increased use of social medial to explore new content (e.g., new information) during lockdowns may have brought about overload and have had a negative impact on academic performance. In the academic activities of college students, the focus on social media platforms may cause an explosion of psychological stress and tiredness, thus weakening their actual performance ( Ayyagari et al., 2011 ). Psychological efforts are required for a good performance in any task ( Boksem and Tops, 2008 ). The performance will decline when people feel tired ( Van der Linden and Eling, 2006 ). Social media overload may have a significantly negative impact on student attention during learning ( Caplan and High, 2006 ). As an example, other studies on American college students have stated that social media overload weakens actual academic performance ( Rosen et al., 2013a , b ; Junco, 2015 ). As reported, teachers commonly worry that social media overload will have a negative impact on the performance of students in various academic activities. Thus, we infer that social media overload has a negative effect on the academic performance of students because it distracts students’ attention from learning.

Based on the above statements, we posit the following hypothesis:

H7 : Social media overload has a negative impact on academic performance.

According to the above hypotheses, the research framework is shown in Figure 1 .

Figure 1 . Research framework.

Data collection

We invited college students to engage in the survey through publishing questionnaires on i.chaoxing.com to collect data online. Every participant was informed that their answers would be kept confidential. Thanks to the suspension of offline courses during the lockdown of the city, data were collected for 2 weeks in September 2021. In order to enhance the sample representativeness, researchers select effective sample clusters based on their research purposes and issues. Thus, purposive sampling is adopted, and several conditions will be established during sampling so as to improve the representativeness of the research samples. First, mainland China, where the pandemic was most severe in the beginning, was selected as the main area for sampling, and the quarantine policy was the strictest. Thus, it is representative to a certain extent. Second, to understand the psychological characteristics of college students, it is necessary to focus on those who actually face boredom proneness. Third, while filling the questionnaire, all the samples were already isolated at home. In order to attract broader participation of college students, we offered a coupon valuing two dollars for each participant who completes the questionnaire. Students were required to provide their student number to avoid the repeat submission. All variables were adopted from prior literature and were measured on a five-point Likert scale with response choices ranging from “Strongly disagree (1)” to “Strongly agree (5)” In order to screen social media users from participants, we design a question: Are you a user of some social media? Only the questionnaires submitted by those who answered yes to this question are considered as the valid ones. A total of 500 students participated in this survey, and 15 of them were excluded from the sample pool because they do not use social media. Besides, additional 44 questionnaires were not completed. As a result, we finally obtained 441 valid samples.

When self-report questionnaires are used to collect data at the same time from the same participants, common method variance (CMV) may be a concern. A post hoc Harman one-factor analysis was used to test for CMV ( Podsakoff and Organ, 1986 ). The explained variance in one factor is 40.554%, which is smaller than the recommended threshold of 50%. Therefore, CMV is not problematic in this study to test the research model, a survey instrument was developed with each construct measured using multiple items ( Harman, 1976 ). Most items were adapted from existing measures in the related literature with confirmed content validity and reliability, and then modified to fit our research context. Boredom proneness was measured by four items adapted from Vodanovich et al. (2005) . Information overload were measured by four items adapted from Karr-Wisniewski and Lu (2010) . Communication overload were measured by four items adapted from Karr-Wisniewski and Lu (2010) . System feature overload was measured by three items adapted from ( Lee et al., 2016 ). Social media overload was measured using Maier et al. (2015) instrument (four items). Academic performance uses the scales (four items) developed by Welbourne et al. (1998) . All items were measured with a five-point Likert scale (1, totally disagree; 5, totally agree).

Evaluation of measurement model

Data analysis was divided into two stages: the reliability and validity of the measurement model were evaluated in the first stage, and the structural model was examined in the second stage to conduct the examination of the research hypotheses ( Hair et al., 2009 ). In this study, the latent variable structural equation models (SMEs) of SmartPLS3.0 and SPSS 25 were adopted as the analysis method. Currently, academics generally agree with the approach of Anderson and Gerbing (1984) . That is, CFA should report Standardized Factor Loading, Multivariate Correlation Squared, Composite Reliability, and Average Variance Extracted for all variables, and only after these metrics pass the test can structural models be evaluated. Currently, academics generally agree with the approach of Anderson and Gerbing (1984) . That is, CFA should report Standardized Factor Loading, Multivariate Correlation Squared, Composite Reliability, and Average Variance Extracted for all variables, and only after these metrics pass the test can structural models be evaluated. Table 1 shows the average number, factor loading, reliability, and average variance extracted (AVE) value of each construct in this study. The composite reliability (CR) of each construct in this study ranged from 0.870 to 0.954, and every Cronbach’s alpha (α) was higher than 0.7, indicating a high reliability for the constructs in this study. AVE ranged from 0.791 to 0.897, which was also greater than 0.500, indicating a good convergent validity for the constructs in this study. Table 2 shows the correlation coefficient matrix for each construct in this study. The square root of the AVE for each construct was greater than the correlation coefficient for the dimensions ( Chin, 1998 ), indicating a good discriminant validity for the constructs in this study. Besides, Henseler et al. (2016) have proposed that the heterotrait-monotrait ratio (HTMT) of correlations based on the multitrait-multimethod matrix could be adopted as a method to determine discriminant validity. Table 3 shows that the HTMT values for the constructs are all lower than 0.9, showing a good discriminant validity for the constructs in this study. The above analysis showed a good construct validity for this study.

Table 1 . Summary of study measures and factor loadings of CFA and SEM.

Table 2 . Matrix of construct correlation coefficients.

Table 3 . Heterotrait-monotrait (HTMT).

Data analysis and results

Smart PLS 3.0 was adopted for the structural model analysis in this study. The value of the standardized root mean square residual (SRMR) can be applied to evaluate the fit of the research model, which is between 0 and 1: the closer it is to 0, the better the fit is. However, the saturated model of the SRMR assumes that the number of paths in the structural model is the same as the number of related constructs in the measurement model, and the estimated model is calculated in terms of the sample dataset itself and the rows. When the SRMR of the saturated model and the estimated model is less than 0.08, it indicates a good fit for the model Hu and Bentler (1999) . The value of the normed fit index (NFI) is between 0 and 1, where the closer it is to 1, the better the fit is, and a value of NFI greater than 0.8 means an acceptable fit.

According to the results calculated by Smart PLS, the value of the SRMR for the saturated model in this study is 0.056, and the value of the SRMR for the estimated model is 0.064, both of which are less than 0.080. The value of NFI is 0.842, which meets the requirements for fit. There is thus a good model fit for this study.

After the evaluation and measurement results were found to be satisfactory, we evaluated the structural model, and examined the hypothesis through the percentage of variance and the significance of structural path. Figure 2 shows the test results of the PLS analysis containing control variables. Boredom Proneness was positively correlated with information overload ( β  = 0.456, p  < 0.001), communication overload ( β  = 0.525, p  < 0.001) and system feature overload ( β  = 0.392, p  < 0.001), thus supporting H1, H2, and H3. Information overload ( β  = 0.253, p  < 0.01) and communication overload ( β  = 0.324, p  < 0.001) had a significant positive correlation with the sense of Social Media Overload, thus supporting H4 and 5. Social media overload ( β  = −0.239, p  < 0.001) was positively correlated with independent academic performance, thus supporting H7. But system feature overload ( β  = 0.018, p  = 0.124) is not significant for social media overload, so H6 is not supported.

Figure 2 . SEM analysis of the research model.

This study reveals that boredom proneness is correlated with social media overload can lead to reduced academic performance among college students. Our analysis of data collected from 441 college students confirms that boredom proneness is positively correlated with information, communication and system feature overloads as well as social media overload and it weaken students’ academic performance.

College students tend to be negatively susceptible to social media because of their flexible timetable, lots of free time and lack of self-control, especially when bored during the quarantine and lockdown period. Recent studies have observed the harmful effects of social media overload ( Lutz et al., 2014 ; Bright et al., 2015 ; Maier et al., 2015 ; Dhir et al., 2018 ), but none of them have given a theoretical explanation on how and why the social media overload leads to reduced performance. This study aims to discuss the impact of social media overload on college students’ academic performance through combining TCIU with the SSO model.

Theoretical significance

As an expansion of prior studies on the SSO model, this study finds that the boredom proneness which appeared among college students during COVID-19 interacted with its resulting social media overload, which further has caused a decline in students’ academic performance. This study makes multiple theoretical contributions. First of all, we combine TCIU with the SSO model to theoretically understand antecedents and outcomes of social media overload. Our study confirms that the use of the SSO model allows us to better understand the validity of digital technologies and education phenomena. Although prior literature has investigated social media overload through the SSO model and stress–strain–outcome model ( Luqman et al., 2017 ; Loh et al., 2021 ), we maintain that the SSO model can better illustrate this complex human behavior.

Second, our research findings show that boredom proneness is positively correlated with overload. In terms of practical implications, the findings from this study can be used as justification for developing targeted interventions that enhance cognitive control abilities so as to avoid social media overload and ultimately impaired performance. Current studies of antecedents of social media overload either place emphasis on demographics and usage characteristics ( Laumer et al., 2014 ) or underline system and information characteristics ( Cho et al., 2011 ; Lee et al., 2016 ). On the contrary, this study verifies the effectiveness of implicit stimuli in explaining social media overload, which means that boredom proneness may finally cause the social media overload that adversely affects college students’ academic performance. Our results show that information overload and communication overload significantly herald social media overload. In essence, social media overload is a transient phenomenon, and it takes a period of time for users to reach the overload state. The inability to control social media use and override impulsive judgments will finally lead to overload. Thus, we conclude that the problematic use of technologies will result in an imbalance between cognitive processes ( Soror et al., 2015 ; Turel et al., 2016 ). This study also finds that social media overload has a negative impact on academic performance. Although most of the prior literature uses social media overload as a mechanism to explain problematic social media use ( LaRose et al., 2003 , 2014 ), our study proves that social media overload will eventually lead to a decline in students’ academic performance, which is an extension of current knowledge.

However, system feature overload has no effect on social media overload, which is contrary to our expectations. Some scholars have indicated that individuals are more willing to use diversified system features to form a relatively special work style and are more tolerant of the corresponding increase in cognitive load and interference caused by system features. In addition, some prior studies also reveal that individuals may be accustomed to continuous and high system function overload after forming an intimate relationship with their mobile devices in life ( Yoo, 2010 ; Bødker et al., 2014 ). As argued in previous studies, system feature overload will reduce as the age lowers ( Zhang et al., 2016 ). A possible explanation is that college students are more interested in social network services, which makes them not susceptible to system feature overload.

Third, by discussing the dark side of social media use among college students, this study has enriched the research on cyber psychology and is beneficial for the development of research on technology stress. In the context of the COVID-19 quarantine, studies on social media overload among college students are urgently needed and are important to offer new insights. College students are a major user group of social media, and the focus of relevant studies is placed on how this group actively engages in social media but seldom on how they wrongly use social media ( Priporas et al., 2017 ; Throuvala et al., 2019 ). Our findings dispel the stereotype that college students can completely take control of social media use on their own, and it foregrounds this generation’s vulnerability in terms of social media use, especially during the pandemic ( Turner, 2015 ). As stated by TCIU, social media have been major recreational tools for college students during the COVID-19 quarantine period. This study attests that overload will result in social media overload from the perspective of users and underlines the potential defects of using social media in college students’ learning processes.

Practical significance

To achieve our goal, we followed the stress-based behavioral theory proposed in the SSO model ( Davis and Luthans, 1980 ). In this process, this study facilitates research on general explanations for the relationship between social media and college students’ academic performance and gives more detailed and specific explanations for the causality. As expected, boredom proneness results in the overload.

This study has the following practical significances. First of all, parents, educators and the public should raise their awareness of the dark side of social media, especially boredom proneness. Parents and educators need to encourage young social media users (e.g., college students and teenagers) to bravely confront their boredom proneness, motivate them to avoid or get rid of negative boredom and support the positive use of social media as motivation.

Second, our study also offers valuable insights for developers of social media systems. It is well-known that social media developers build in features to distract users from alternate tasks in order to increase fixation with their own service. We found that these overloads lead to social media overload among students, and ultimately negatively affects their academic performance. Other studies report overloaded users are more likely stop using the service altogether. Thus, it makes business sense for social media providers to incorporate features in their service which assist the user in avoiding overload.

Third, although this study does not support the influence of system feature overload on social media overload, we still recommend that social media providers facilitate a smooth transition by announcing the changed schedule and scope in advance to reduce discomfort. Besides, social media providers can also provide user guides to introduce new features to users. It is even suggested that SNS providers allow users to design their own SNS accounts instead of developing complex accounts and then integrating embedded features into these accounts.

Research limitations and research prospects

There are some limitations to this study. First of all, data were collected at four universities in a particular country, i.e., China. The research results may be different if other age groups, cultural backgrounds and pandemic quarantine stages are considered. To eliminate this limitation, we suggest that other scholars include a similar research model, other age groups with different cultural backgrounds and all the stages of the pandemic in their studies. Second, this is a cross-sectional study that collects data from online groups, so there is the issue of method bias (e.g., selection and response bias), and possible changes to given relationships within a period of time cannot be reflected. To address this limitation and considering the continuity of the pandemic, we suggest using a longitudinal method and/or qualitative method to further explore psychological health and the effects of social media use. Third, overload is considered to be a harmful psychological state in this study, and social media overload is considered as the behavioral outcome of the information overload on social media. However, previous research on the dark side of social media use reveals that psychological illnesses also include other aspects, such as anxiety, depression and tiredness ( Dhir et al., 2018 ; Evers et al., 2020 ), as well as sleep problems ( Dhir et al., 2019 ; Malik et al., 2020 ; Tandon et al., 2020 ). Consequently, we advocate for other scholars to expand the findings of this study by taking other relevant issues into account. Likewise, scholars can also explore how to improve individuals’ psychological well-being and mental health by making use of social media during the pandemic. Finally, gender has been an important influencing factor for studies of college students behaviors, because male students may have a different grasp of social media overload from female students. As a result, this study suggests to consider comparisons between males and females to offer richer and more valuable significance to the development of theoretical models.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by Academic Committee of Fujian University of Technology. The patients/participants provided their written informed consent to participate in this study.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Fujian Social Science Planning youth project. Research on the development mechanism of agricultural e-commerce industry in Fujian Province from the perspective of big data (FJ2020C062).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: boredom proneness, information overload, communication overload, system feature overload, academic performance

Citation: Xu Y, Li Y, Zhang Q, Yue X and Ye Y (2022) Effect of social media overload on college students’ academic performance under the COVID-19 quarantine. Front. Psychol . 13:890317. doi: 10.3389/fpsyg.2022.890317

Received: 05 March 2022; Accepted: 02 August 2022; Published: 29 August 2022.

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Copyright © 2022 Xu, Li, Zhang, Yue and Ye. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xianghua Yue, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Social Media: Does Usage Have Impact on Academic Performance?

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Does the More Social Media Usage Good Academic Grade? Meta-Analysis

Social learning theory, findings on facebook in higher education: a comparison of college faculty and student uses and perceptions of social networking sites, short-term and long-term consequences of achievement goals: predicting interest and performance over time., facebook and the others. potentials and obstacles of social media for teaching in higher education, the role of feedback and self-efficacy on web-based learning: the social cognitive perspective, related papers (5), the effects of social media on pharmacy students’ academic performances, the effect of social media use on the academic success and attitude of students, effect of social media on college students academic performance, a real-time observation approach for assessing the impact of social media on students’ academic performance, the impact of social media use on academic performance at one urban university: a pilot study, trending questions (3).

The study found that social media usage intensity has a negative impact on students' academic performance.

The social learning theory suggests that the intensity of social media usage may influence students' academic performance.

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Analysing the Impact of Social Media on Students’ Academic Performance: A Comparative Study of Extraversion and Introversion Personality

• Review Article
• Published: 12 November 2022
• Volume 67 , pages 549–559, ( 2022 )

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• Sourabh Sharma   ORCID: orcid.org/0000-0002-9729-5129 1 &
• Ramesh Behl 1  

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The advent of technology in education has seen a revolutionary change in the teaching–learning process. Social media is one such invention which has a major impact on students’ academic performance. This research analyzed the impact of social media on the academic performance of extraversion and introversion personality students. Further, the comparative study between these two personalities will be analysed on education level (postgraduate and undergraduate) and gender (male and female). The research was initiated by identifying the factors of social media impacting students’ academic performance. Thereafter, the scale was developed, validated and tested for reliability in the Indian context. Data were collected from 408 students segregated into 202 males and 206 females. Two hundred and thirty-four students are enrolled in postgraduation courses, whereas 174 are registered in the undergraduate programme. One-way ANOVA has been employed to compare the extraversion and introversion students of different education levels and gender. A significant difference is identified between extraversion and introversion students for the impact of social media on their academic performance.

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Introduction

Social Networking Sites (SNS) gained instant popularity just after the invention and expansion of the Internet. Today, these sites are used the most to communicate and spread the message. The population on these social networking sites (SNS) has increased exponentially. Social networking sites (SNS) in general are called social media (Boyd & Ellison, 2008 ). Social media (SM) is used extensively to share content, initiate discussion, promote businesses and gain advantages over traditional media. Technology plays a vital role to make SM more robust by reducing security threats and increasing reliability (Stergiou et al., 2018 ).

As of January 2022, more than 4.95 billion people are using the Internet worldwide, and around 4.62 billion are active SM users (Johnson, 2022 ). In India, the number of Internet users was 680 million by January 2022, and there were 487 million active social media users (Basuray, 2022 ). According to Statista Research Department ( 2022 ), in India, SM is dominated by two social media sites, i.e. YouTube and Facebook. YouTube has 467 million users followed by Facebook with 329 million users.

Although almost all age groups are using SM platforms to interact and communicate with their known community (Whiting & Williams, 2013 ), it has been found that social media sites are more popular among youngsters and specifically among students. They use SM for personal as well as academic activities extensively (Laura et al., 2017 ). Other than SM, from the last two years, several online platforms such as Microsoft Teams, Zoom and Google Meet are preferred to organize any kind of virtual meetings, webinars and online classes. These platforms were used worldwide to share and disseminate knowledge across the defined user community during the pandemic. Social media sites such as Facebook, YouTube, Instagram, WhatsApp and blogs are comparatively more open and used to communicate with public and/or private groups. Earlier these social media platforms were used only to connect with friends and family, but gradually these platforms became one of the essential learning tools for students (Park et al., 2009 ). To enhance the teaching–learning process, these social media sites are explored by all types of learning communities (Dzogbenuku et al., 2019 ). SM when used in academics has both advantages and disadvantages. Social media helps to improve academic performance, but it may also distract the students from studies and indulge them in other non-academic activities (Alshuaibi et al., 2018 ).

Here, it is important to understand that the personality traits of students, their education level and gender are critical constructs to determine academic performance. There are different personality traits of an individual such as openness, conscientiousness, extraversion and introversion, agreeableness and neuroticism (McCrae & Costa, 1987 ). This cross-functional research is an attempt to study the impact of social media on the academic performance of students while using extraversion and introversion personality traits, education levels and gender as moderating variables.

Literature Review

There has been a drastic change in the internet world due to the invention of social media sites in the last ten years. People of all age groups now share their stories, feelings, videos, pictures and all kinds of public stuff on social media platforms exponentially (Asur & Huberman, 2010 ). Youth, particularly from the age group of 16–24, embraced social media sites to connect with their friends and family, exchange information and showcase their social status (Boyd & Ellison, 2008 ). Social media sites have many advantages when used in academics. The fun element of social media sites always helps students to be connected with peers and teachers to gain knowledge (Amin et al., 2016 ). Social media also enhances the communication between teachers and students as this are no ambiguity and miscommunication from social media which eventually improves the academic performance of the students (Oueder & Abousaber, 2018 ).

When social media is used for educational purposes, it may improve academic performance, but some associated challenges also come along with it (Rithika & Selvaraj, 2013 ). If social media is incorporated into academics, students try to also use it for non-academic discussions (Arnold & Paulus, 2010 ). The primary reason for such distraction is its design as it is designed to be a social networking tool (Qiu et al., 2013 ). According to Englander et al. ( 2010 ), the usage of social media in academics has more disadvantages than advantages. Social media severely impacts the academic performance of a student. The addiction to social media is found more among the students of higher studies which ruins the academic excellence of an individual (Nalwa & Anand, 2003 ). Among the social media users, Facebook users’ academic performance was worse than the nonusers or users of any other social media network. Facebook was found to be the major distraction among students (Kirschner & Karpinski, 2010 ). However, other studies report contrary findings and argued that students benefited from chatting (Jain et al., 2012 ), as it improves their vocabulary and writing skills (Yunus & Salehi, 2012 ). Social media can be used either to excel in academics or to devastate academics. It all depends on the way it is used by the students. The good or bad use of social media in academics is the users’ decision because both the options are open to the students (Landry, 2014 ).

Kaplan and Haenlein ( 2010 ) defined social media as user-generated content shared on web 2.0. They have also classified social media into six categories:

Social Networking Sites: Facebook, Twitter, LinkedIn and Instagram are the social networking sites where a user may create their profile and invite their friends to join. Users may communicate with each other by sharing common content.

Blogging Sites: Blogging sites are individual web pages where users may communicate and share their knowledge with the audience.

Content Communities and Groups: YouTube and Slideshare are examples of content communities where people may share media files such as pictures, audio and video and PPT presentations.

Gaming Sites: Users may virtually participate and enjoy the virtual games.

Virtual Worlds: During COVID-19, this type of social media was used the most. In the virtual world, users meet with each other at some decided virtual place and can do the pre-decided things together. For example, the teacher may decide on a virtual place of meeting, and students may connect there and continue their learning.

Collaborative Content Sites: Wikipedia is an example of a collaborative content site. It permits many users to work on the same project. Users have all rights to edit and add the new content to the published project.

Massive open online courses (MOOCs) are in trend since 2020 due to the COVID-19 pandemic (Raja & Kallarakal, 2020 ). MOOCs courses are generally free, and anyone may enrol for them online. Many renowned institutions have their online courses on MOOCs platform which provides a flexible learning opportunity to the students. Students find them useful to enhance their knowledge base and also in career development. Many standalone universities have collaborated with the MOOCs platform and included these courses in their curriculum (Chen, 2013 ).

Security and privacy are the two major concerns associated with social media. Teachers are quite apprehensive in using social media for knowledge sharing due to the same concerns (Fedock et al., 2019 ). It was found that around 72% teachers were reluctant to use social media platforms due to integrity issues and around 63% teachers confirmed that security needs to be tightened before using social media in the classroom (Surface et al., 2014 ). Proper training on security and privacy, to use social media platforms in academics, is needed for  students and teachers (Bhatnagar & Pry, 2020 ).

The personality traits of a student also play a significant role in deciding the impact of social media on students’ academic performance. Personality is a dynamic organization which simplifies the way a person behaves in a situation (Phares, 1991 ). Human behaviour has further been described by many renowned researchers. According to Lubinski ( 2000 ), human behaviour may be divided into five factors, i.e. cognitive abilities, personality, social attitudes, psychological interests and psychopathology. These personality traits are very important characteristics of a human being and play a substantial role in work commitment (Macey & Schneider, 2008 ). Goldberg ( 1993 ) elaborated on five dimensions of personality which are commonly known as the Big Five personality traits. The traits are “openness vs. cautious”; “extraversion vs. introversion”; “agreeableness vs. rational”; “conscientiousness vs. careless”; and “neuroticism vs. resilient”.

It has been found that among all personality traits, the “extraversion vs. introversion” personality trait has a greater impact on students’ academic performance (Costa & McCrae, 1999 ). Extrovert students are outgoing, talkative and assertive (Chamorro et al., 2003 ). They are positive thinkers and comfortable working in a crowd. Introvert students are reserved and quiet. They prefer to be isolated and work in silos (Bidjerano & Dai, 2007 ). So, in the present study, we have considered only the “extraversion vs. introversion” personality trait. This study is going to analyse the impact of social media platforms on students’ academic performance by taking the personality trait of extraversion and introversion as moderating variables along with their education level and gender.

Research Gap

Past research by Choney ( 2010 ), Karpinski and Duberstein ( 2009 ), Khan ( 2009 ) and Kubey et al. ( 2001 ) was done mostly in developed countries to analyse the impact of social media on the students’ academic performance, effect of social media on adolescence, and addictiveness of social media in students. There are no published research studies where the impact of social media was studied on students’ academic performance by taking their personality traits, education level and gender all three together into consideration. So, in the present study, the impact of social media will be evaluated on students’ academic performance by taking their personality traits (extraversion and introversion), education level (undergraduate and postgraduate) and gender (male and female) as moderating variables.

Objectives of the Study

Based on the literature review and research gap, the following research objectives have been defined:

To identify the elements of social media impacting student's academic performance and to develop a suitable scale

To test the  validity and reliability of the scale

To analyse the impact of social media on students’ academic performance using extraversion and introversion personality trait, education level and gender as moderating variables

Research Methodology

Sampling technique.

Convenience sampling was used for data collection. An online google form was floated to collect the responses from 408 male and female university students of undergraduation and postgraduation streams.

Objective 1 To identify the elements of social media impacting student's academic performance and to develop a suitable scale.

A structured questionnaire was employed to collect the responses from 408 students of undergraduate and postgraduate streams. The questionnaire was segregated into three sections. In section one, demographic details such as gender, age and education stream were defined. Section two contained the author’s self-developed 16-item scale related to the impact of social media on the academic performance of students. The third section had a standardized scale developed by John and Srivastava ( 1999 ) of the Big Five personality model.

Demographics

There were 408 respondents (students) of different education levels consisting of 202 males (49.5%) and 206 females (50.5%). Most of the respondents (87%) were from the age group of 17–25 years. 234 respondents (57.4) were enrolled on postgraduation courses, whereas 174 respondents (42.6) were registered in the undergraduate programme. The result further elaborates that WhatsApp with 88.6% and YouTube with 82.9% are the top two commonly used platforms followed by Instagram with 76.7% and Facebook with 62.3% of students. 65% of students stated that Google doc is a quite useful and important application in academics for document creation and information dissemination.

Validity and Reliability of Scale

Objective 2 Scale validity and reliability.

Exploratory factor analysis (EFA) and Cronbach’s alpha test were used to investigate construct validity and reliability, respectively.

The author’s self-designed scale of ‘social media impacting students’ academic performance’ consisting of 16 items was validated using exploratory factor analysis. The principle component method with varimax rotation was applied to decrease the multicollinearity within the items. The initial eigenvalue was set to be greater than 1.0 (Field, 2005 ). Kaiser–Meyer–Olkin (KMO) with 0.795 and Bartlett’s test of sphericity having significant values of 0.000 demonstrated the appropriateness of using exploratory factor analysis.

The result of exploratory factor analysis and Cronbach’s alpha is shown in Table 1 . According to Sharma and Behl ( 2020 ), “High loading on the same factor and no substantial cross-loading confirms convergent and discriminant validity respectively”.

The self-developed scale was segregated into four factors, namely “Accelerating Impact”, “Deteriorating Impact”, “Social Media Prospects” and “Social Media Challenges”.

The first factor, i.e. “Accelerating Impact”, contains items related to positive impact of social media on students’ academic performance. Items in this construct determine the social media contribution in the grade improvement, communication and knowledge sharing. The second factor “Deteriorating Impact” describes the items which have a negative influence of social media on students’ academic performance. Items such as addiction to social media and distraction from studies are an integral part of this factor. “Social Media Prospects” talk about the opportunities created by social media for students’ communities. The last factor “Social Media Challenges” deals with security and privacy issues created by social media sites and the threat of cyberbullying which is rampant in academics.

The personality trait of an individual always influences the social media usage pattern. Therefore, the impact of social media on the academic performance of students may also change with their personality traits. To measure the personality traits, the Big Five personality model was used. This model consists of five personality traits, i.e. “openness vs. cautious”; “extraversion vs. introversion”; “agreeableness vs. rational”; “conscientiousness vs. careless”; and “neuroticism vs. resilient”. To remain focussed on the scope of the study, only a single personality trait, i.e. “extraversion vs. introversion” with 6 items was considered for analysis. A reliability test of this existing scale using Cronbach’s alpha was conducted. Prior to the reliability test, reverse scoring applicable to the associated items was also calculated. Table 2 shows the reliability score, i.e. 0.829.

Objective 3 To analyse the impact of social media on students’ academic performance using extraversion and introversion personality traits, education level and gender as moderating variables.

The research model shown in Fig.  1 helps in addressing the above objective.

Social media factors impacting academic performances of extraversion and introversion personality traits of students at different education levels and gender

As mentioned in Fig.  1 , four dependent factors (Accelerating Impact, Deteriorating Impact, Social Media Prospects and Social Media Challenges) were derived from EFA and used for analysing the impact of social media on the academic performance of students having extraversion and introversion personality traits at different education levels and gender.

Students having a greater average score (more than three on a scale of five) for all personality items mentioned in Table 2 are considered to be having extraversion personality or else introversion personality. From the valid dataset of 408 students, 226 students (55.4%) had extraversion personality trait and 182 (44.6%) had introversion personality trait. The one-way ANOVA analysis was employed to determine the impact of social media on academic performance for all three moderators, i.e. personality traits (Extraversion vs. Introversion), education levels (Undergraduate and Postgraduate) and gender (Male and Female). If the sig. value for the result is >  = 0.05, we may accept the null hypothesis, i.e. there is no significant difference between extraversion and introversion personality students for the moderators; otherwise, null hypothesis is rejected which means there is a significant difference for the moderators.

Table 3 shows the comparison of the accelerating impact of social media on the academic performance of all students having extraversion and introversion personality traits. It also shows a comparative analysis on education level and gender for these two personality traits of students. In the first comparison of extraversion and introversion students, the sig. value is 0.001, which indicates that there is a significant difference among extraversion and introversion students for the “Accelerating Impact” of social media on academic performance. Here, 3.781 is the mean value for introversion students which is higher than the mean value 3.495 of extraversion students. It clearly specifies that the accelerating impact of social media is more prominent in the students having introversion personality traits. Introversion students experienced social media as the best tool to express thoughts and improve academic grades. The result is also consistent with the previous studies where introvert students are perceived to use social media to improve their academic performance (Amichai-Hamburger et al., 2002 ; Voorn & Kommers, 2013 ). Further at the education level, there was a significant difference in postgraduate as well as undergraduate students for the accelerating impact of social media on the academic performance among students with extraversion and introversion, and introverts seem to get better use of social media. The gender-wise significant difference was also analysed between extraversion and introversion personalities. Female introversion students were found to gain more of an accelerating impact of social media on their academic performance.

Like Table 3 , the first section of Table 4 compares the deteriorating impact of social media on the academic performance of all students having extraversion and introversion personality traits. Here, the sig. value 0.383 indicates no significant difference among extraversion and introversion students for the “Deteriorating Impact” of social media on academic performance. The mean values show the moderating deteriorating impact of social media on the academic performance of extraversion and introversion personality students. Unlimited use of social media due to the addiction is causing a distraction in academic performance, but the overall impact is not on the higher side. Further, at the education level, the sig. values 0.423 and 0.682 of postgraduate and undergraduate students, respectively, show no significant difference between extraversion and introversion students with respect to “Deteriorating Impact of Social Media Sites”. The mean values again represent the moderate impact. Gender-wise, male students have no difference between the two personality traits, but at the same time, female students have a significant difference in the deteriorating impact, and it is more on extroverted female students.

The significant value, i.e. 0.82, in Table 5 represents no significant difference between extraversion and introversion personality students for the social media prospects. The higher mean value of both personality students indicates that they are utilizing the opportunities of social media in the most appropriate manner. It seems that all the students are using social media for possible employment prospects, gaining knowledge by attending MOOCs courses and transferring knowledge among other classmates. At the education level, postgraduation students have no significant difference between extraversion and introversion for the social media prospects, but at the undergraduate level, there is a significant difference among both the personalities, and by looking at mean values, extroverted students gain more from the social media prospects. Gender-wise comparison of extraversion and introversion personality students found no significant difference in the social media prospects for male as well as female students.

Table 6 shows the comparison of the social media challenges of all students having extraversion and introversion personality traits. It is also doing a comparative analysis on education level and gender for these two personality traits of students. All sig. values in Table 6 represent no significant difference between extraversion and introversion personality students for social media challenges. Even at the education level and gender-wise comparison of the two personalities, no significant difference is derived. The higher mean values indicate that the threat of cyberbullying, security and privacy is the main concern areas for extraversion and introversion personality students. Cyberbullying is seen to be more particularly among female students (Snell & Englander, 2010 ).

The use of social media sites in academics is becoming popular among students and teachers. The improvement or deterioration in academic performance is influenced by the personality traits of an individual. This study has tried to analyse the impact of social media on the academic performance of extraversion and introversion personality students. This study has identified four factors of social media which have an impact on academic performance. These factors are: accelerating impact of social media; deteriorating impact of social media; social media prospects; and social media challenges.

Each of these factors has been used for comparative analysis of students having extraversion and introversion personality traits. Their education level and gender have also been used to understand the detailed impact between these two personality types. In the overall comparison, it has been discovered that both personalities (extraversion and introversion) have a significant difference for only one factor, i.e. “Accelerating Impact of Social Media Sites” where students with introversion benefited the most. At the education level, i.e. postgraduate and undergraduate, there was a significant difference between extraversion and introversion personalities for the first factor which is the accelerating impact of social media. Here, the introversion students were found to benefit in postgraduate as well as undergraduate courses. For the factors of deteriorating impact and social media challenges, there was no significant difference between extraversion and introversion personality type at the different education levels.

Surprisingly, for the first factor, i.e. the accelerating impact of social media, in gender-wise comparison, no significant difference was found between extraversion and introversion male students. Whereas a significant difference was found in female students. The same was the result for the second factor, i.e. deteriorating impact of social media of male and female students. For social media prospects and social media challenges, no significant difference was identified between extraversion and introversion students of any gender.

Findings and Implications

The personality trait of a student plays a vital role in analysing the impact of social media on their academic performance. The present study was designed to find the difference between extraversion and introversion personality types in students for four identified factors of social media and their impact on students’ academic performance. The education level and gender were also added to make it more comprehensive. The implications of this study are useful for institutions, students, teachers and policymakers.

This study will help the institutions to identify the right mix of social media based on the personality, education level and gender of the students. For example, technological challenges are faced by all students. It is important for the institutions to identify the challenges such as cyberbullying, security and privacy issues and accordingly frame the training sessions for all undergraduate and postgraduate students. These training sessions will help students with extraversion and introversion to come out from possible technological hassles and will create a healthy ecosystem (Okereke & Oghenetega, 2014 ).

Students will also benefit from this study as they will be conscious of the possible pros and cons that exist because of social media usage and its association with students’ academic performance. This learning may help students to enhance their academic performance with the right use of social media sites. The in-depth knowledge of all social media platforms and their association with academics should be elucidated to the students so that they may explore the social media opportunities in an optimum manner. Social media challenges also need to be made known to the students to improve upon and overcome with time (Boateng & Amankwaa, 2016 ).

Teachers are required to design the curriculum by understanding the learning style of students with extraversion and introversion personality type. Innovation and customization in teaching style are important for the holistic development of students and to satisfy the urge for academic requirements. Teachers should also guide the students about the adverse impacts of each social media platform, so that these can be minimized. Students should also be guided to reduce the time limit of using social media (Owusu-Acheaw & Larson, 2015 ).

Policymakers are also required to understand the challenges faced by the students while using social media in academics. All possible threats can be managed by defining and implementing transparent and proactive policies. As social media sites are open in nature, security and privacy are the two major concerns. The Government of India should take a strong stand to control all big social media companies so that they may fulfil the necessary compliances related to students’ security and privacy (Kumar & Pradhan, 2018 ).

The overall result of these comparisons gives a better insight and deep understanding of the significant differences between students with extraversion and introversion personality type towards different social media factors and their impact on students’ academic performance. Students’ behaviour according to their education level and gender for extraversion and introversion personalities has also been explored.

Limitation and Future Scope of Research

Due to COVID restrictions, a convenient sampling technique was used for data collection which may create some response biases where the students of introversion personality traits may have intentionally described themselves as extroversion personalities and vice versa. This study also creates scope for future research. In the Big Five personality model, there are four other personality traits which are not considered in the present study. There is an opportunity to also use cross-personality comparisons for the different social media parameters. The other demographic variables such as age and place may also be explored in future research.

Availability of data and material

Complete data and material is available to support transparency.

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Sharma, S., Behl, R. Analysing the Impact of Social Media on Students’ Academic Performance: A Comparative Study of Extraversion and Introversion Personality. Psychol Stud 67 , 549–559 (2022). https://doi.org/10.1007/s12646-022-00675-6

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The effect of social media on the development of students’ affective variables

1 Science and Technology Department, Nanjing University of Posts and Telecommunications, Nanjing, China

2 School of Marxism, Hohai University, Nanjing, Jiangsu, China

3 Government Enterprise Customer Center, China Mobile Group Jiangsu Co., Ltd., Nanjing, China

The use of social media is incomparably on the rise among students, influenced by the globalized forms of communication and the post-pandemic rush to use multiple social media platforms for education in different fields of study. Though social media has created tremendous chances for sharing ideas and emotions, the kind of social support it provides might fail to meet students’ emotional needs, or the alleged positive effects might be short-lasting. In recent years, several studies have been conducted to explore the potential effects of social media on students’ affective traits, such as stress, anxiety, depression, and so on. The present paper reviews the findings of the exemplary published works of research to shed light on the positive and negative potential effects of the massive use of social media on students’ emotional well-being. This review can be insightful for teachers who tend to take the potential psychological effects of social media for granted. They may want to know more about the actual effects of the over-reliance on and the excessive (and actually obsessive) use of social media on students’ developing certain images of self and certain emotions which are not necessarily positive. There will be implications for pre- and in-service teacher training and professional development programs and all those involved in student affairs.

Introduction

Social media has turned into an essential element of individuals’ lives including students in today’s world of communication. Its use is growing significantly more than ever before especially in the post-pandemic era, marked by a great revolution happening to the educational systems. Recent investigations of using social media show that approximately 3 billion individuals worldwide are now communicating via social media ( Iwamoto and Chun, 2020 ). This growing population of social media users is spending more and more time on social network groupings, as facts and figures show that individuals spend 2 h a day, on average, on a variety of social media applications, exchanging pictures and messages, updating status, tweeting, favoring, and commenting on many updated socially shared information ( Abbott, 2017 ).

Researchers have begun to investigate the psychological effects of using social media on students’ lives. Chukwuere and Chukwuere (2017) maintained that social media platforms can be considered the most important source of changing individuals’ mood, because when someone is passively using a social media platform seemingly with no special purpose, s/he can finally feel that his/her mood has changed as a function of the nature of content overviewed. Therefore, positive and negative moods can easily be transferred among the population using social media networks ( Chukwuere and Chukwuere, 2017 ). This may become increasingly important as students are seen to be using social media platforms more than before and social networking is becoming an integral aspect of their lives. As described by Iwamoto and Chun (2020) , when students are affected by social media posts, especially due to the increasing reliance on social media use in life, they may be encouraged to begin comparing themselves to others or develop great unrealistic expectations of themselves or others, which can have several affective consequences.

Considering the increasing influence of social media on education, the present paper aims to focus on the affective variables such as depression, stress, and anxiety, and how social media can possibly increase or decrease these emotions in student life. The exemplary works of research on this topic in recent years will be reviewed here, hoping to shed light on the positive and negative effects of these ever-growing influential platforms on the psychology of students.

Significance of the study

Though social media, as the name suggests, is expected to keep people connected, probably this social connection is only superficial, and not adequately deep and meaningful to help individuals feel emotionally attached to others. The psychological effects of social media on student life need to be studied in more depth to see whether social media really acts as a social support for students and whether students can use social media to cope with negative emotions and develop positive feelings or not. In other words, knowledge of the potential effects of the growing use of social media on students’ emotional well-being can bridge the gap between the alleged promises of social media and what it actually has to offer to students in terms of self-concept, self-respect, social role, and coping strategies (for stress, anxiety, etc.).

Exemplary general literature on psychological effects of social media

Before getting down to the effects of social media on students’ emotional well-being, some exemplary works of research in recent years on the topic among general populations are reviewed. For one, Aalbers et al. (2018) reported that individuals who spent more time passively working with social media suffered from more intense levels of hopelessness, loneliness, depression, and perceived inferiority. For another, Tang et al. (2013) observed that the procedures of sharing information, commenting, showing likes and dislikes, posting messages, and doing other common activities on social media are correlated with higher stress. Similarly, Ley et al. (2014) described that people who spend 2 h, on average, on social media applications will face many tragic news, posts, and stories which can raise the total intensity of their stress. This stress-provoking effect of social media has been also pinpointed by Weng and Menczer (2015) , who contended that social media becomes a main source of stress because people often share all kinds of posts, comments, and stories ranging from politics and economics, to personal and social affairs. According to Iwamoto and Chun (2020) , anxiety and depression are the negative emotions that an individual may develop when some source of stress is present. In other words, when social media sources become stress-inducing, there are high chances that anxiety and depression also develop.

Charoensukmongkol (2018) reckoned that the mental health and well-being of the global population can be at a great risk through the uncontrolled massive use of social media. These researchers also showed that social media sources can exert negative affective impacts on teenagers, as they can induce more envy and social comparison. According to Fleck and Johnson-Migalski (2015) , though social media, at first, plays the role of a stress-coping strategy, when individuals continue to see stressful conditions (probably experienced and shared by others in media), they begin to develop stress through the passage of time. Chukwuere and Chukwuere (2017) maintained that social media platforms continue to be the major source of changing mood among general populations. For example, someone might be passively using a social media sphere, and s/he may finally find him/herself with a changed mood depending on the nature of the content faced. Then, this good or bad mood is easily shared with others in a flash through the social media. Finally, as Alahmar (2016) described, social media exposes people especially the young generation to new exciting activities and events that may attract them and keep them engaged in different media contexts for hours just passing their time. It usually leads to reduced productivity, reduced academic achievement, and addiction to constant media use ( Alahmar, 2016 ).

The number of studies on the potential psychological effects of social media on people in general is higher than those selectively addressed here. For further insights into this issue, some other suggested works of research include Chang (2012) , Sriwilai and Charoensukmongkol (2016) , and Zareen et al. (2016) . Now, we move to the studies that more specifically explored the effects of social media on students’ affective states.

Review of the affective influences of social media on students

Vygotsky’s mediational theory (see Fernyhough, 2008 ) can be regarded as a main theoretical background for the support of social media on learners’ affective states. Based on this theory, social media can play the role of a mediational means between learners and the real environment. Learners’ understanding of this environment can be mediated by the image shaped via social media. This image can be either close to or different from the reality. In the case of the former, learners can develop their self-image and self-esteem. In the case of the latter, learners might develop unrealistic expectations of themselves by comparing themselves to others. As it will be reviewed below among the affective variables increased or decreased in students under the influence of the massive use of social media are anxiety, stress, depression, distress, rumination, and self-esteem. These effects have been explored more among school students in the age range of 13–18 than university students (above 18), but some studies were investigated among college students as well. Exemplary works of research on these affective variables are reviewed here.

In a cross-sectional study, O’Dea and Campbell (2011) explored the impact of online interactions of social networks on the psychological distress of adolescent students. These researchers found a negative correlation between the time spent on social networking and mental distress. Dumitrache et al. (2012) explored the relations between depression and the identity associated with the use of the popular social media, the Facebook. This study showed significant associations between depression and the number of identity-related information pieces shared on this social network. Neira and Barber (2014) explored the relationship between students’ social media use and depressed mood at teenage. No significant correlation was found between these two variables. In the same year, Tsitsika et al. (2014) explored the associations between excessive use of social media and internalizing emotions. These researchers found a positive correlation between more than 2-h a day use of social media and anxiety and depression.

Hanprathet et al. (2015) reported a statistically significant positive correlation between addiction to Facebook and depression among about a thousand high school students in wealthy populations of Thailand and warned against this psychological threat. Sampasa-Kanyinga and Lewis (2015) examined the relationship between social media use and psychological distress. These researchers found that the use of social media for more than 2 h a day was correlated with a higher intensity of psychological distress. Banjanin et al. (2015) tested the relationship between too much use of social networking and depression, yet found no statistically significant correlation between these two variables. Frison and Eggermont (2016) examined the relationships between different forms of Facebook use, perceived social support of social media, and male and female students’ depressed mood. These researchers found a positive association between the passive use of the Facebook and depression and also between the active use of the social media and depression. Furthermore, the perceived social support of the social media was found to mediate this association. Besides, gender was found as the other factor to mediate this relationship.

Vernon et al. (2017) explored change in negative investment in social networking in relation to change in depression and externalizing behavior. These researchers found that increased investment in social media predicted higher depression in adolescent students, which was a function of the effect of higher levels of disrupted sleep. Barry et al. (2017) explored the associations between the use of social media by adolescents and their psychosocial adjustment. Social media activity showed to be positively and moderately associated with depression and anxiety. Another investigation was focused on secondary school students in China conducted by Li et al. (2017) . The findings showed a mediating role of insomnia on the significant correlation between depression and addiction to social media. In the same year, Yan et al. (2017) aimed to explore the time spent on social networks and its correlation with anxiety among middle school students. They found a significant positive correlation between more than 2-h use of social networks and the intensity of anxiety.

Also in China, Wang et al. (2018) showed that addiction to social networking sites was correlated positively with depression, and this correlation was mediated by rumination. These researchers also found that this mediating effect was moderated by self-esteem. It means that the effect of addiction on depression was compounded by low self-esteem through rumination. In another work of research, Drouin et al. (2018) showed that though social media is expected to act as a form of social support for the majority of university students, it can adversely affect students’ mental well-being, especially for those who already have high levels of anxiety and depression. In their research, the social media resources were found to be stress-inducing for half of the participants, all university students. The higher education population was also studied by Iwamoto and Chun (2020) . These researchers investigated the emotional effects of social media in higher education and found that the socially supportive role of social media was overshadowed in the long run in university students’ lives and, instead, fed into their perceived depression, anxiety, and stress.

Keles et al. (2020) provided a systematic review of the effect of social media on young and teenage students’ depression, psychological distress, and anxiety. They found that depression acted as the most frequent affective variable measured. The most salient risk factors of psychological distress, anxiety, and depression based on the systematic review were activities such as repeated checking for messages, personal investment, the time spent on social media, and problematic or addictive use. Similarly, Mathewson (2020) investigated the effect of using social media on college students’ mental health. The participants stated the experience of anxiety, depression, and suicidality (thoughts of suicide or attempts to suicide). The findings showed that the types and frequency of using social media and the students’ perceived mental health were significantly correlated with each other.

The body of research on the effect of social media on students’ affective and emotional states has led to mixed results. The existing literature shows that there are some positive and some negative affective impacts. Yet, it seems that the latter is pre-dominant. Mathewson (2020) attributed these divergent positive and negative effects to the different theoretical frameworks adopted in different studies and also the different contexts (different countries with whole different educational systems). According to Fredrickson’s broaden-and-build theory of positive emotions ( Fredrickson, 2001 ), the mental repertoires of learners can be built and broadened by how they feel. For instance, some external stimuli might provoke negative emotions such as anxiety and depression in learners. Having experienced these negative emotions, students might repeatedly check their messages on social media or get addicted to them. As a result, their cognitive repertoire and mental capacity might become limited and they might lose their concentration during their learning process. On the other hand, it should be noted that by feeling positive, learners might take full advantage of the affordances of the social media and; thus, be able to follow their learning goals strategically. This point should be highlighted that the link between the use of social media and affective states is bi-directional. Therefore, strategic use of social media or its addictive use by students can direct them toward either positive experiences like enjoyment or negative ones such as anxiety and depression. Also, these mixed positive and negative effects are similar to the findings of several other relevant studies on general populations’ psychological and emotional health. A number of studies (with general research populations not necessarily students) showed that social networks have facilitated the way of staying in touch with family and friends living far away as well as an increased social support ( Zhang, 2017 ). Given the positive and negative emotional effects of social media, social media can either scaffold the emotional repertoire of students, which can develop positive emotions in learners, or induce negative provokers in them, based on which learners might feel negative emotions such as anxiety and depression. However, admittedly, social media has also generated a domain that encourages the act of comparing lives, and striving for approval; therefore, it establishes and internalizes unrealistic perceptions ( Virden et al., 2014 ; Radovic et al., 2017 ).

It should be mentioned that the susceptibility of affective variables to social media should be interpreted from a dynamic lens. This means that the ecology of the social media can make changes in the emotional experiences of learners. More specifically, students’ affective variables might self-organize into different states under the influence of social media. As for the positive correlation found in many studies between the use of social media and such negative effects as anxiety, depression, and stress, it can be hypothesized that this correlation is induced by the continuous comparison the individual makes and the perception that others are doing better than him/her influenced by the posts that appear on social media. Using social media can play a major role in university students’ psychological well-being than expected. Though most of these studies were correlational, and correlation is not the same as causation, as the studies show that the number of participants experiencing these negative emotions under the influence of social media is significantly high, more extensive research is highly suggested to explore causal effects ( Mathewson, 2020 ).

As the review of exemplary studies showed, some believed that social media increased comparisons that students made between themselves and others. This finding ratifies the relevance of the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ) and Festinger’s (1954) Social Comparison Theory. Concerning the negative effects of social media on students’ psychology, it can be argued that individuals may fail to understand that the content presented in social media is usually changed to only represent the attractive aspects of people’s lives, showing an unrealistic image of things. We can add that this argument also supports the relevance of the Social Comparison Theory and the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ), because social media sets standards that students think they should compare themselves with. A constant observation of how other students or peers are showing their instances of achievement leads to higher self-evaluation ( Stapel and Koomen, 2000 ). It is conjectured that the ubiquitous role of social media in student life establishes unrealistic expectations and promotes continuous comparison as also pinpointed in the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ).

Implications of the study

The use of social media is ever increasing among students, both at school and university, which is partly because of the promises of technological advances in communication services and partly because of the increased use of social networks for educational purposes in recent years after the pandemic. This consistent use of social media is not expected to leave students’ psychological, affective and emotional states untouched. Thus, it is necessary to know how the growing usage of social networks is associated with students’ affective health on different aspects. Therefore, we found it useful to summarize the research findings in recent years in this respect. If those somehow in charge of student affairs in educational settings are aware of the potential positive or negative effects of social media usage on students, they can better understand the complexities of students’ needs and are better capable of meeting them.

Psychological counseling programs can be initiated at schools or universities to check upon the latest state of students’ mental and emotional health influenced by the pervasive use of social media. The counselors can be made aware of the potential adverse effects of social networking and can adapt the content of their inquiries accordingly. Knowledge of the potential reasons for student anxiety, depression, and stress can help school or university counselors to find individualized coping strategies when they diagnose any symptom of distress in students influenced by an excessive use of social networking.

Admittedly, it is neither possible to discard the use of social media in today’s academic life, nor to keep students’ use of social networks fully controlled. Certainly, the educational space in today’s world cannot do without the social media, which has turned into an integral part of everybody’s life. Yet, probably students need to be instructed on how to take advantage of the media and to be the least affected negatively by its occasional superficial and unrepresentative content. Compensatory programs might be needed at schools or universities to encourage students to avoid making unrealistic and impartial comparisons of themselves and the flamboyant images of others displayed on social media. Students can be taught to develop self-appreciation and self-care while continuing to use the media to their benefit.

The teachers’ role as well as the curriculum developers’ role are becoming more important than ever, as they can significantly help to moderate the adverse effects of the pervasive social media use on students’ mental and emotional health. The kind of groupings formed for instructional purposes, for example, in social media can be done with greater care by teachers to make sure that the members of the groups are homogeneous and the tasks and activities shared in the groups are quite relevant and realistic. The teachers cannot always be in a full control of students’ use of social media, and the other fact is that students do not always and only use social media for educational purposes. They spend more time on social media for communicating with friends or strangers or possibly they just passively receive the content produced out of any educational scope just for entertainment. This uncontrolled and unrealistic content may give them a false image of life events and can threaten their mental and emotional health. Thus, teachers can try to make students aware of the potential hazards of investing too much of their time on following pages or people that publish false and misleading information about their personal or social identities. As students, logically expected, spend more time with their teachers than counselors, they may be better and more receptive to the advice given by the former than the latter.

Teachers may not be in full control of their students’ use of social media, but they have always played an active role in motivating or demotivating students to take particular measures in their academic lives. If teachers are informed of the recent research findings about the potential effects of massively using social media on students, they may find ways to reduce students’ distraction or confusion in class due to the excessive or over-reliant use of these networks. Educators may more often be mesmerized by the promises of technology-, computer- and mobile-assisted learning. They may tend to encourage the use of social media hoping to benefit students’ social and interpersonal skills, self-confidence, stress-managing and the like. Yet, they may be unaware of the potential adverse effects on students’ emotional well-being and, thus, may find the review of the recent relevant research findings insightful. Also, teachers can mediate between learners and social media to manipulate the time learners spend on social media. Research has mainly indicated that students’ emotional experiences are mainly dependent on teachers’ pedagogical approach. They should refrain learners from excessive use of, or overreliance on, social media. Raising learners’ awareness of this fact that individuals should develop their own path of development for learning, and not build their development based on unrealistic comparison of their competences with those of others, can help them consider positive values for their activities on social media and, thus, experience positive emotions.

At higher education, students’ needs are more life-like. For example, their employment-seeking spirits might lead them to create accounts in many social networks, hoping for a better future. However, membership in many of these networks may end in the mere waste of the time that could otherwise be spent on actual on-campus cooperative projects. Universities can provide more on-campus resources both for research and work experience purposes from which the students can benefit more than the cyberspace that can be tricky on many occasions. Two main theories underlying some negative emotions like boredom and anxiety are over-stimulation and under-stimulation. Thus, what learners feel out of their involvement in social media might be directed toward negative emotions due to the stimulating environment of social media. This stimulating environment makes learners rely too much, and spend too much time, on social media or use them obsessively. As a result, they might feel anxious or depressed. Given the ubiquity of social media, these negative emotions can be replaced with positive emotions if learners become aware of the psychological effects of social media. Regarding the affordances of social media for learners, they can take advantage of the potential affordances of these media such as improving their literacy, broadening their communication skills, or enhancing their distance learning opportunities.

A review of the research findings on the relationship between social media and students’ affective traits revealed both positive and negative findings. Yet, the instances of the latter were more salient and the negative psychological symptoms such as depression, anxiety, and stress have been far from negligible. These findings were discussed in relation to some more relevant theories such as the social comparison theory, which predicted that most of the potential issues with the young generation’s excessive use of social media were induced by the unfair comparisons they made between their own lives and the unrealistic portrayal of others’ on social media. Teachers, education policymakers, curriculum developers, and all those in charge of the student affairs at schools and universities should be made aware of the psychological effects of the pervasive use of social media on students, and the potential threats.

It should be reminded that the alleged socially supportive and communicative promises of the prevalent use of social networking in student life might not be fully realized in practice. Students may lose self-appreciation and gratitude when they compare their current state of life with the snapshots of others’ or peers’. A depressed or stressed-out mood can follow. Students at schools or universities need to learn self-worth to resist the adverse effects of the superficial support they receive from social media. Along this way, they should be assisted by the family and those in charge at schools or universities, most importantly the teachers. As already suggested, counseling programs might help with raising students’ awareness of the potential psychological threats of social media to their health. Considering the ubiquity of social media in everybody’ life including student life worldwide, it seems that more coping and compensatory strategies should be contrived to moderate the adverse psychological effects of the pervasive use of social media on students. Also, the affective influences of social media should not be generalized but they need to be interpreted from an ecological or contextual perspective. This means that learners might have different emotions at different times or different contexts while being involved in social media. More specifically, given the stative approach to learners’ emotions, what learners emotionally experience in their application of social media can be bound to their intra-personal and interpersonal experiences. This means that the same learner at different time points might go through different emotions Also, learners’ emotional states as a result of their engagement in social media cannot be necessarily generalized to all learners in a class.

As the majority of studies on the psychological effects of social media on student life have been conducted on school students than in higher education, it seems it is too soon to make any conclusive remark on this population exclusively. Probably, in future, further studies of the psychological complexities of students at higher education and a better knowledge of their needs can pave the way for making more insightful conclusions about the effects of social media on their affective states.

Suggestions for further research

The majority of studies on the potential effects of social media usage on students’ psychological well-being are either quantitative or qualitative in type, each with many limitations. Presumably, mixed approaches in near future can better provide a comprehensive assessment of these potential associations. Moreover, most studies on this topic have been cross-sectional in type. There is a significant dearth of longitudinal investigation on the effect of social media on developing positive or negative emotions in students. This seems to be essential as different affective factors such as anxiety, stress, self-esteem, and the like have a developmental nature. Traditional research methods with single-shot designs for data collection fail to capture the nuances of changes in these affective variables. It can be expected that more longitudinal studies in future can show how the continuous use of social media can affect the fluctuations of any of these affective variables during the different academic courses students pass at school or university.

As already raised in some works of research reviewed, the different patterns of impacts of social media on student life depend largely on the educational context. Thus, the same research designs with the same academic grade students and even the same age groups can lead to different findings concerning the effects of social media on student psychology in different countries. In other words, the potential positive and negative effects of popular social media like Facebook, Snapchat, Twitter, etc., on students’ affective conditions can differ across different educational settings in different host countries. Thus, significantly more research is needed in different contexts and cultures to compare the results.

There is also a need for further research on the higher education students and how their affective conditions are positively and negatively affected by the prevalent use of social media. University students’ psychological needs might be different from other academic grades and, thus, the patterns of changes that the overall use of social networking can create in their emotions can be also different. Their main reasons for using social media might be different from school students as well, which need to be investigated more thoroughly. The sorts of interventions needed to moderate the potential negative effects of social networking on them can be different too, all requiring a new line of research in education domain.

Finally, there are hopes that considering the ever-increasing popularity of social networking in education, the potential psychological effects of social media on teachers be explored as well. Though teacher psychology has only recently been considered for research, the literature has provided profound insights into teachers developing stress, motivation, self-esteem, and many other emotions. In today’s world driven by global communications in the cyberspace, teachers like everyone else are affecting and being affected by social networking. The comparison theory can hold true for teachers too. Thus, similar threats (of social media) to self-esteem and self-worth can be there for teachers too besides students, which are worth investigating qualitatively and quantitatively.

Probably a new line of research can be initiated to explore the co-development of teacher and learner psychological traits under the influence of social media use in longitudinal studies. These will certainly entail sophisticated research methods to be capable of unraveling the nuances of variation in these traits and their mutual effects, for example, stress, motivation, and self-esteem. If these are incorporated within mixed-approach works of research, more comprehensive and better insightful findings can be expected to emerge. Correlational studies need to be followed by causal studies in educational settings. As many conditions of the educational settings do not allow for having control groups or randomization, probably, experimental studies do not help with this. Innovative research methods, case studies or else, can be used to further explore the causal relations among the different features of social media use and the development of different affective variables in teachers or learners. Examples of such innovative research methods can be process tracing, qualitative comparative analysis, and longitudinal latent factor modeling (for a more comprehensive view, see Hiver and Al-Hoorie, 2019 ).

Author contributions

Both authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

This study was sponsored by Wuxi Philosophy and Social Sciences bidding project—“Special Project for Safeguarding the Rights and Interests of Workers in the New Form of Employment” (Grant No. WXSK22-GH-13). This study was sponsored by the Key Project of Party Building and Ideological and Political Education Research of Nanjing University of Posts and Telecommunications—“Research on the Guidance and Countermeasures of Network Public Opinion in Colleges and Universities in the Modern Times” (Grant No. XC 2021002).

Conflict of interest

Author XX was employed by China Mobile Group Jiangsu Co., Ltd. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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