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Social Media. A Literature Review

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Abstract. The development and expansion of social media have rapidly changed the interaction and communication of people, thereby attracting attention in an unprecedented scale. This paper reviews the relevant literature on social media to yield a better understanding of how it has transformed the way people communicate, acquire and use information. To elucidate on the goals of this paper, the definition of social media, and its characteristics are presented. Different types of social media are also described, including globally popular platforms based on social media types in the 21st century. Lastly, a brief review of the research on social media was presented to provide a reference for researchers.

Keywords: Social media; Social network; Communication tool; Literature review.

Introduction

In the recent years, social media is described as a global phenomenon. There are billions of social media users worldwide and this number keeps on growing. According to the report of Statista in 2020, Eastern Asia has the largest share of social media audiences worldwide with 1.07 billion active users. Among them, China is the biggest social media market with 926.8 million users, India stands at the ranked second with nearly 350 million users (Clement, 2020, July 15).

Social media touches nearly every facet of people's life, allows users to connect with like-minded people and provide information of interest to them. Social media also affects how businesses conduct their transactions, promotions, and services (Bhimani et al., 2018; Appel et al., 2020). These show the proliferation of social media as well as the growing interest for it from both researchers and and practitioners (Kapoor et al., 2018; Ghania et al., 2019). Thus, the number of published articles related to social media is constantly increasing (Olanrewaju, 2020). Along with that, numerous literature review papers on social media have been conducted. These existing papers focus on specific subjects from different fields as marketing (Paquette, 2013; Khan & Jan, 2015), innovation (Bhimani et al., 2018), educational (Chugh & Ruhi, 2018; Ahmed, 2019) or health care (Zhao & Zhang, 2017; Ukoha & Stranieri, 2019). It is in this interest that this paper reviewed relevant studies in different fields to provide a clearer understanding of the intricacies of social media.

The structure of this paper is as follows: first, the definition of...

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How can mobile social media sustain consumers assessing the dynamic influences of differentiated perceived interactivity on attitudes, belongingness, and stickiness.

1. Introduction

2. theoretical framework and hypotheses development, 2.1. linking perceived interactivity to consumer attitudes, 2.2. linking consumer attitudes to consumer belongingness, 2.3. linking consumer attitudes and consumer belongingness to stickiness, 3. research methodology, 3.1. research model, 3.2. measurement, 3.3. sample and data collection, 4.1. measurement model, reliability, and validity, 4.2. common method variance testing, 4.3. structural model, 5. discussion, 5.1. conclusions, 5.2. theoretical and practical implications, 6. limitations and implications for future research, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Pang, H.; Ruan, Y.; Wang, L. How Can Mobile Social Media Sustain Consumers? Assessing the Dynamic Influences of Differentiated Perceived Interactivity on Attitudes, Belongingness, and Stickiness. J. Theor. Appl. Electron. Commer. Res. 2024 , 19 , 2783-2798. https://doi.org/10.3390/jtaer19040134

Pang H, Ruan Y, Wang L. How Can Mobile Social Media Sustain Consumers? Assessing the Dynamic Influences of Differentiated Perceived Interactivity on Attitudes, Belongingness, and Stickiness. Journal of Theoretical and Applied Electronic Commerce Research . 2024; 19(4):2783-2798. https://doi.org/10.3390/jtaer19040134

Pang, Hua, Yang Ruan, and Lei Wang. 2024. "How Can Mobile Social Media Sustain Consumers? Assessing the Dynamic Influences of Differentiated Perceived Interactivity on Attitudes, Belongingness, and Stickiness" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 4: 2783-2798. https://doi.org/10.3390/jtaer19040134

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A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion

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• Published: 14 February 2022
• Volume 81 , pages 10107–10142, ( 2022 )

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• Maud Reveilhac   ORCID: orcid.org/0000-0001-9769-6830 1 ,
• Stephanie Steinmetz   ORCID: orcid.org/0000-0001-7136-6622 1 &
• Davide Morselli   ORCID: orcid.org/0000-0003-3231-7769 1 , 2  

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In this article, we review existing research on the complementarity of social media data and survey data for the study of public opinion. We start by situating our review in the extensive literature (N = 187) about the uses, challenges, and frameworks related to the use of social media for studying public opinion. Based on 187 relevant articles (141 empirical and 46 theoretical) - we identify within the 141 empircal ones six main research approaches concerning the complementarity of both data sources. Results show that the biggest share of the research has focused on how social media can be used to confirm survey findings, especially for election predictions. The main contribution of our review is to detail and classify other growing complementarity approaches, such as comparing both data sources on a given phenomenon, using survey measures as a proxy in social media research, enriching surveys with SMD, recruiting individuals on social media to conduct a second survey phase, and generating new insight on “old” or “under-investigated” topics or theories using SMD. We discuss the advantages and disadvantages associated with each of these approaches in relation to four main research purposes, namely the improvement of validity, sustainability, reliability, and interpretability. We conclude by discussing some limitations of our study and highlighting future paths for research.

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1 Introduction

This paper provides a systematic literature review of how social media data (SMD) and traditional survey data have been used complementarily to study public opinion (PO) over the last decade. As social media users represent more than half of the world’s population (see [ 26 ]) and provide continuous reactions to daily socio-political events, it is not surprising that traditional survey research has been concerned about whether such data would make surveys obsolete or whether they could be used complementarily. Addressing these questions is particularly relevant in the area of PO. Social media plays a growing role in the formation of PO as user-generated content on these platforms is increasingly deployed as representations of PO (e.g. [ 27 , 56 ]). In addition, politicians increasingly consider social media, especially Twitter, to be a “barometer” of PO [ 44 ].

Despite the extensive literature about the benefits and challenges of using SMD to answer social and political questions, as well as about SMD as a possible replacement for traditional surveys, a comprehensive overview of the complementarity of both data sources remains limited. The aim of this paper is to fill this gap by providing a systematic literature review focusing on how SMD and survey data can complement each other to study PO. Inspired by the influential study of Japec et al. [ 45 ] which elaborated on the complementarity of survey data and “big data” (rather broadly defined), we want to concentrate, however, on one type of “big data”, namely SMD. There are two main reasons for this choice. First, SMD are a specific type of “non-survey” data which possess specific arrangements (or conventions) and paradata that are different from other types of administrative or “big data”, especially when it come to the assessment of PO. Second, whereas there is substantial research on augmenting survey data with administrative (e.g. electricity or water consumption) or other type of “web data” (e.g. Google searches or citation metrics) to improve estimates of PO or official statistics, we still lack an overarching picture of the (new) developments and approaches of complementing SMD and surveys with each other.

Our analysis is based on an extensive survey of the literature capturing a representative sample of the best published theoretical and empirical scientific papers on the topic (N = 187). We have restricted the analytical period to the last decade (2010–2020) as the discussion on complementarity is still a young field of study (e.g. [ 58 ]). On this basis, we have been able to identify six complementarity approaches which can be synthesised to four major purposes, namely predicting, substituting, comparing, and linking SMD and survey data.

In the next section, we situate our review within the existing literature by demonstrating how the scientific discussion surrounding the opportunities and challenges offered by SMD within survey research has evolved, especially by highlighting the complementary understanding of PO offered by both data sources. Then, we discuss more specifically which research approaches have emerged, and we classify them according to four main research purposes using both data sources complementarily. The analysis of the empirical studies aims to act as a guide for other researchers by identifying research gaps and highlighting the pros and cons of each approach. Furthermore, we underline areas for future improvements and point to technical and ethical considerations. We conclude by mentioning the main contributions and limitations of our review.

2 Background – The complementary understandings of PO

Surveys have long been the most predictive and accurate tools for collecting and measuring opinion. However, over the last decade, decreasing response rates have called into question the potential of using a random sample of individuals to represent an entire population (e.g. [ 37 , 49 ]), thus posing important concerns about the sustainability of survey research. Even by adapting to new modes, such as push-to-web, to increase response rates, it remains unclear whether surveys will maintain this dominant role as communication habits continue to change (e.g. [ 68 ]). Given the recent “survey crisis” (e.g. [ 13 , 22 ]), an increasingly rich source of PO data is commonly referred to as “big data”. These “new” data take the form of extraordinarily large and complex datasets. There are three attributes that are generally agreed upon to describe this type of data (e.g. [ 19 ]), namely volume, velocity, and variety. Social media are a sub-type of big data where people express their thoughts and opinions with the purpose of sharing them with others [ 18 ]. Due to their inherent properties, SMD have been seen as a promising complementary, and even alternative, source of data for exploring PO. However, researchers acknowledged early on that, almost universally, SMD are non-random, and thus discouraged using them as a means of making generalisable claims. This challenge is well highlighted by Schober et al. [ 68 ], who claim that, while the social media researcher seeks to achieve topic coverage, the survey researcher emphasises population coverage as a central endeavour.

An entire strand of research thus focussed on how surveys and social media differ in several aspects. Table 1 attempts to classify the most prominent differences along which SMD and survey data are typically compared. We have identified several dimensions based on recurring criteria mentioned in the literature concerning the nature of and the relationship between both data sources. Often-cited criteria include the type of population and data signal, the unit of observation and analysis, and the available meta-data (for a thorough discussion of the differences see [ 18 , 68 ], and [ 77 ]).

To understand how to best use both data sources complementarily, it is also essential to reflect on how they construct PO differently. This is increasingly important, as what constitutes “the public” tends to be forged by the methods and data from which it is derived [ 56 ]. In survey research, PO is equivalent to the private opinion of a representative public, operationalised as a set of positions on a given topic. PO can thus be conceptualised as a reflection of a shared position among citizens on specific issues that are then amplified and reviewed by news media and political actors [ 42 ]. Survey measures of PO are constrained by the scope of the questionnaires, which usually provide little room for spontaneous expressions of opinion (except in open-ended survey questions). The diversity of opinions is thereby reduced into a set of discrete and aggregate data (e.g. [ 75 ]). Conversely, the reliance on social media for measuring PO expands the societal and collective components of opinions [ 59 ] by conceptualising it in Habermas’ [ 39 ] terms as a complex system of representations. In this respect, SMD are better suited to capturing the conversational and relational nature of PO formation [ 3 ]. Hence, where survey data weigh precision and standardisation, SMD excel in multidimensionality and polyphony. In addition to their focus on solicited private opinions, surveys are also less reactive to opinion changes than SMD. In theory, opinion changes could be assessed by frequent short opinion surveys (e.g. every two months). However, the advantage of SMD is that they can cover opinion change more rapidly (and on an ad hoc basis), thus reacting faster to events, which is almost impossible for surveys (e.g. it takes more time to set up probability-based surveys for the study of COVID compared to what can be done with SMD).

Despite the advantages offered by social media for measuring more social and timelier opinions, the reliance on SMD raises important questions for empirical research on (automated) measurements of opinions and on the choice of the indicators employed to model opinions. Indeed, constructing measures of PO based on SMD can be very time consuming and can involve a lot of pre-processing effort before the data can be translated into meaningful measures of expressed opinions. Furthermore, it sometimes remains quite difficult to know what is driving the evolution of ideas and concerns found in online conversations. Consequently, a current strand of research seeks to better understand the issues of representativeness of social media communities and the validity of measured opinion, especially opinions stemming from sentiment analysis. While there is a rising interest in applying SMD to understand opinion, and even to replace traditional surveys (e.g. [ 3 , 32 ]), SMD alone are of limited use for social scientific research as they usually provide incomplete and imprecise information. However, the issues associated with SMD are not necessarily fatal to the proposition that they can be used to generate social insights, especially in complementing survey data. An efficient strategy to enhance research lies, therefore, in the analysis of how both data sources can complement each other in ways that maximise their strengths.

In the next sections, we aim to show that there is a plethora of research practices in which both data sources complement each other for the study of PO. To date, however, there is still no consensus about the best way to use SMD for studying PO [ 58 ]. We are now at a point where we should reflect on what has been done so far, what lessons we can learn from it, and then specify suitable trends for social research. In this paper, we seek to fill this gap by reviewing research that uses both data sources complementarily for the purposes of measuring PO and by providing a critical evaluation of the identified research paths.

3 Method of analysis: Building a corpus of relevant articles

To build our corpus of scientific articles, we carried out several searches in bibliographic databases (focusing on Scopus and Google Scholar ) using the software PublishOrPerish [ 40 ]. We obtained an initial corpus of 3596 unique papers, which we reduced to papers that were relevant for the scope of our review. The initial corpus was deliberately based on a search-query that was broad enough to collect the relevant literature, while not missing important papers. We used the query “(social media OR twitter OR facebook OR instagram OR reddit) AND (survey OR surveys OR polls)” and specified that it should appear in the body of the text (using the keyword field) instead of appearing only in the title or abstract, which were found to be too restrictive to capture the literature of interest. The query was designed to restrict the focus of our review to SMD, thus ignoring other types of “big data” or “digital trace” data.

A first filter was applied to reduce the number of papers to journal articles, book chapters, and scientific reports (thus excluding books, theses, and conference papers) as we wanted to concentrate on high-valued scientific sources which have already been approved by the scientific community. In this respect, including conference papers would have drastically inflated the number of (duplicated) papers concerned with predictions and with replicating previous studies using alternative methods of analysis and algorithms. Among the remaining papers, we applied two eligibility criteria to disregard those that were not pertinent to the analysis as i) their focus was not on PO, ii) they were oriented towards a specific aspect of data treatment (e.g. estimating socio-demographics from texts or profile pictures) or an analytical strategy (e.g. elaborating algorithms). We also excluded articles mentioning survey findings without an explicit aim of supplementing, comparing, or combining those with SMD.

4 Results of the literature review on the uses of social media as a complement to surveys

Overall, the collection protocol left us with 187 papers - 141 of an empirical and 46 of a theoretical nature (these papers can be found in the Appendix). Most of these papers stem from political communication and computational social sciences journals. Although the sample of 187 papers may not cover the whole corpus of research on the subject, it is nonetheless sufficient to highlight the main research directions that have been endorsed on the topic of complementarity. Figure 1 provides an overview of the yearly repartition of the retrieved papers differentiating between those with a theoretical (N = 46) and an empirical (N = 141) focus. While the number of theoretical papers remains stable over the years, we can see a steady increase in empirical papers over time.

Number of empirical and theoretical articles according to our meta-review of the existing literature using surveys and SMD

4.1 Theoretical insights

Starting with the theoretical papers in our review (N = 46, see Table 2 in the Appendix), survey and social media researchers have explored ways in which social media and survey data can yield congruent conclusions (e.g. [ 68 ]). One part of these articles (n = 14) tries to establish a framework regarding the predictive power of SMD as a potential substitute for surveys. This line of research stems principally from the fields of election and economy forecasting (for recent reviews see [ 15 , 66 ]).

Another strand of theoretical articles (n = 14) focuses instead on the compliance of social media research with established reporting standards so as to guarantee transparency and replicability (e.g. [ 51 ]). Finding ways of integrating data obtained from different sources (n = 3) also constitutes a fertile path of research [ 46 ]. In this respect, Stier et al. [ 72 ] provide the most advanced guide on how to systematically link survey data with information from external data sources, including SMD, at different level of analysis. The authors demonstrate that integrating traditional survey data and digital trace data is of growing interest, notably because of the limited reliability of self-reported behavioural measures and declining response rates. Additionally, enriching survey data with SMD could also help to reduce unit non-response and to control for the unrepresentativeness of SMD, as they are limited to those respondents having social media profiles and consenting to the linkage. Finally, a smaller share of research (n = 5) focuses on developing a quality assessment framework for SMD which is similar to the Total Survey Error (TSE) [ 11 , 38 ]. The TSE framework has been extended to encompass SMD and their inherent quality challenges (see the studies by Sen et al. [ 70 ] on Twitter-based studies and Jungherr [ 47 ] for a measurement theory to account for the pitfalls of digital traces). In a similar vein, Hsieh and Murphy [ 43 ] analysed the potential benefits of evaluating estimates from surveys and SMD in common terms and arrived at a general error framework for Twitter opinion research. Olteanu et al. [ 61 ] went a step further by pointing to the errors and biases that could potentially affect studies based on digital behavioural data, outlining them in an idealised study framework. The paper by Sen et al. [ 70 ] provides the most advanced framework to date. It involves potential measurement and representation errors in a digital trace-based study lifecycle where they are classified according to their sources.

Other research (n = 5) tackles the ontology of SMD as compared to survey data. In these papers, prevalent discussions revolve around the conception of opinion as measured by both data sources, as well as debates related to the evolution of “new” research “paradigms” or “digital hermeneutics”. The remaining papers concentrate on behavioural research (n = 2), demographic research (n = 2), and small data analysis in political communication (n = 1).

Overall, the considered theoretical articles stress the importance of developing a framework that accounts for possible biases of SMD while remaining in, or mirroring, the TSE. Moreover, they also emphasize the need, in this debate, to focus on the complementarity rather than the replacing aspect, notably by developing clear and reliable linking strategies. These articles also encourage researchers to go beyond the dominant model for understanding PO from probability sample surveys to encompass other (“new”) expressions of opinions (e.g. Murphy et al. 2014) that can possibly supplement or even replace survey-based approaches.

4.2 Empirical insights

The empirical literature (N = 141) focuses on a rather narrow set of topics, such as elections, political issues, and approval ratings for the presidency (64%). Another important area of PO research using SMD complementarily with survey data is related to health (e.g. vaccination, drugs, etc.), equality issues, and climate or environment-related concerns. Most empirical studies in our review are based on Twitter data (73%), followed by Facebook (18%) and other social media (9%). This is related to the fact that not all social media platforms provide the same degree of data accessibility [ 8 ]. For instance, Facebook imposes severe limitations on the scope of retrievable data, whereas Twitter has less strong privacy settings, allowing researchers to get access to Twitter’s historical data.

Overall, we derived six major approaches on how survey data and SMD can complement each other namely i) predicting social and political outcomes using SMD (n = 48), ii) comparing both data sources on a given phenomenon (n = 26), iii) using survey measures as a proxy in social media research (n = 18), iv) enriching surveys with SMD (n = 9), v) recruiting individuals on social media to conduct a second survey phase (n = 8), and vi) generating new insight on “old” or “under-investigated” topics or theories using SMD (n = 32). These approaches can be synthesised in four, partly overlapping, ‘data complementing’ research purposes: i) validating survey findings with SMD, ii) improving the sustainability of the research by diversifying the views on a phenomenon, iii) improving the reliability of survey measures by specifying measurements, and iv) improving the interpretability of social or political issues. Figure 2 summarises the relationship between the six approaches and the four research purposes. Furthermore, it shows that each purpose leads to a typical way of using both data sources complementarily. For instance, improving reliability by specifying a research question involves data linkage strategies, while generating new insights involves a sequential use of social media and survey stages.

Complementary approaches using SMD and survey data for the study of PO

The analysis of our corpus suggests that the biggest part of research concentrates on whether SMD can potentially substitute survey data (n = 48, see Table 3 in the Appendix). This has mostly been done by trying to replicate survey findings by using SMD for forecasting (see recent review by [ 66 ]). The aim to predict real-world outcomes with SMD in the realm of PO has essentially been applied to elections. Most of these papers directly refer to the much-cited study of O’Connor et al. [ 60 ] which purpose is to validate SMD against survey findings. While research in this area has tested a range of different methodologies, the results remain inconclusive, and only in some cases could elections be accurately predicted (e.g. [ 31 , 47 ]). Recent literature reviews on the use of SMD for running electoral predictions (e.g. [ 15 ]) classify studies according to the employed methods of prediction, such as volume, sentiment, or network approaches. These reviews show considerable variance in the accuracy of predictions, which, on average, lag behind the established survey measurements. A common problem of the aforementioned studies lies in the decision about which approach can most accurately yield predictions (but also which social media platforms are better suited, and how that varies in different geographical or temporal contexts). This inference problem is quite complex as various elements are involved in skewing the samples in social media debates. To date, the inconclusive state of the research has led to a research agenda aiming to respond to the plea from Gayo-Avello et al. [ 33 ] for a “model explaining the predictive power of social media” (p. 490). In this realm, for instance, the study of Pasek et al. (2019) assesses how patterns of approval among population subgroups compare to tweets about the president, while disentangling effects at the individual and group levels of analysis. On a more theoretical level, the study by Schober et al. [ 69 ] seeks to elaborate when and under what conditions SMD can be used to make valid inferences. However, the inconclusive state of the research may also be linked to the fact that predictions are often done based on the content created by users and overlook the characteristics of the creating users. For instance, SMD can be biased towards a particular group (see [ 5 , 24 ]). Moreover, interactions on social media platforms are not always the product of individuals, but also bots, organisations, political parties, etc. [ 80 ]. Based on the evaluation of the body of articles falling under the ‘substitution paradigm’, a path for future research could be to better account for the characteristics of social media users, insofar as these characteristics can be useful for assessing how individual tweets can be converted into meaningful measures of expressed opinion. To do so, future studies could survey social media users identified using relevant key terms (e.g. hashtags or mentions) to gauge the relationship between social media measures of their sentiment and survey measures of their attitudes.

The second dominant approach in our review is related to how surveys can be enriched with SMD (n = 9, see Table 4 in the Appendix). Here, SMD are collected with the intention of improving the reliability of survey measures at the individual or aggregate level. Replication of survey-based opinions can be difficult, either because of improper interpretation of the findings or because insufficient information has been provided. Such issues undermine the credibility of survey research and make it difficult to evaluate the contributions of a given study. Research aiming to enrich surveys with SMD most often implies the adoption of a data-linking strategy. This can be done, for instance, either at the user level, public actor level, geographic level, or temporal level (see [ 72 ]). Enriching surveys with SMD can serve several goals. First, it can help to augment the explanatory potential of survey measures. For instance, De Sio & Weber [ 23 ] adopted an innovative research design to explain election outcomes based on party strategy on social media with respect to policy issue salience. They did this by linking representative mass surveys from six European countries with Twitter analysis of campaign activity. Second, enrichment of survey data with SMD can also help to test research hypotheses by relying on “true” behavioural measures (instead of self-reported survey measures). For instance, Karlsen and Enjolras [ 48 ] linked candidate survey data with Twitter data to study styles of social media campaigning. These differences in campaigning styles were then related to the extent to which candidates were successful on Twitter. Third, SMD also offer an opportunity to address issues of item non-response and calibration of novel measures. For instance, Shin [ 71 ] studied the extent to which social media users selectively consumed like-minded news stories by linking survey responses from Twitter users with their media following and exposure to news via their friends. The study further showed some differences between self-reports and digital measures, such as more pronounced patterns of selective exposure in the SMD. Finally, linking social survey and SMD further provides an opportunity to explore the relationship between attitudes and beliefs reported through surveys and content (and behaviours) generated online. For instance, Cardenal et al. [ 14 ] combined survey and Web-tracking data to analyse how Facebook-referred news consumption influenced social media users’ agendas. They found that selective exposure increased with amplified news consumption. The core problem in these studies lies in gaining consent to carry out the data linkage. This constitutes a complex procedure in which issues of anonymity, security, and disclosure all come to the fore. An additional problem is that social media measurements provide only one partial view of opinions. For instance, while researchers can measure how many times a given message has been liked, shared, or retweeted, it is much harder to account for (or measure) how often a given message has been seen or has attracted attention. Moreover, our corpus shows that research relying on linking strategies tends to remain at the individual and public actor levels of analysis, which requires requesting consent to use the linked data. This may, in turn, introduce consent or selection bias. To mitigate such difficulties, future studies should also explore the potentials of linking both data sources at higher levels of analysis, such as country or according to topicality level.

A third purpose is to use surveys as a proxy in social media research. This approach therefore reverses the logic that SMD are always used as a complementary (side) element of the main survey-based analyses. In this kind of “survey proxy approach” (n = 18, see Table 5 in the Appendix), SMD are used as the main source of analysis, while the survey data are used for contextualising or calibrating SMD. A first strand of research relies on SMD to complement traditional research approaches in political communication and citizens’ political engagement. For instance, the assessment of the importance of given public concerns in PO has been measured extensively with the “most important problem” survey item. Social media provide another way to measure this concern in an unintrusive way by (semi-)automatically classifying the content of social media texts, while also accounting for the extent to which different actors are responsive to these concerns. Following this logic, the study conducted by Eberl et al. [ 28 ] investigated the effects of sentiment and issue salience on emotionally labelled responses to posts written by political actors on Facebook. Another study, by Plescia et al. [ 64 ], analysed the responsiveness of populist parties to the issue salience amongst the public. They did this by relying on survey data to measure public salience and tweets to assess salience issue for parties. A second strand of studies aims at facilitating cross-national comparisons. For instance, a possible application consists in using survey data for classifying parties and voters along important dimensions (e.g. see [ 30 ]). Here, parties were placed on a left and right spectrum using the Chapel Hill Expert Survey [ 4 ]. Party score on the overall ideological stance was then used as an explanatory variable in subsequent analysis. Another example is the study by Park et al. [ 62 ] which investigated the consumption of popular YouTube videos in countries that differ in cultural values, language, gross domestic product, and Internet penetration rate. A possible issue encountered by these studies is linked to spurious effects between survey and social media measurements (e.g. misleading or unexplained correlations). Furthermore, these studies tend to remain poorly equipped to explain actual motives behind social media users’ expression of opinions or reactions. The “survey as proxy” approach requires a considerable dose of ingenuity and methodological innovation to mine social media for producing opinion estimates that can be merged with survey estimates. For instance, SMD corpora often deviate from a predefined (survey) coding scheme. Substantively, a future path of research should take advantage of the fact that a growing number of societal issues have become transnational, such as immigration, terrorism, women’s rights, and climate change. Such research could involve the combination of word embeddings and survey opinion measures at the country level.

A fourth approach aims to compare SMD with survey responses that directly measure PO. Studies comparing SMD with survey data (n = 26, see Table 6 in Appendix) essentially aim at improving sustainability of the research, which consists in the ability to gauge PO consistently over time. Sustainability thus implies that we should develop designs that include opportunities for “holistic merging” of the data that will generate more inclusive and fine-grained research insights. There are several reasons that comparing both data sources is meaningful for social research. Firstly, comparing SMD and survey data can be very useful in times of protests and collective actions, notably due to the difficulty of generating survey data to properly assess these disruptive changes (see critique of survey data by Lee [ 53 ]). The timing of an event might indeed not coincide with the timing of a survey, which is often done ex-post. For instance, Davis et al. [ 21 ] examined the extent to which tweets about the affordable care act (“Obamacare”) could be used to measure PO over time. Secondly, social media can be compared to surveys for research questions that require chronicity, on a weekly or daily basis, thus going beyond the few ongoing surveys that collect data monthly or yearly. For instance, Diaz et al. [ 25 ] demonstrated how social media activity functions like an “opt-in panel” where users repeatedly discuss the same topics. This allows us to study, longitudinally, quite rapid shifts in individual opinions and behaviours, thus complementing survey panels which are prohibitively expensive. Another example is the study by Loureiro & Alló [ 54 ], which aimed to complement surveys by providing up-to-date measurements about social concerns when debating mitigation and energy transition paths. Thirdly, survey questions are often designed to capture internal attitudes toward a specific object. However, the relevance of certain survey questions might vary over time and, in some cases, might no longer correspond to the issues discussed spontaneously online. For instance, at a geographical level, the study by Scarborough [ 67 ] compared gender equality attitudes found in survey data to sentiments emanating from tweets. Fourth, SMD can produce quicker and less expensive statistics for enabling informed policy and program decisions. However, this requires gaining knowledge of where any possible disparities in attitude distributions between SMD and survey data may lie. In this respect, the study by Amaya et al. [ 2 ] presented recent advancements. The authors compared attitude distributions between Reddit users and survey measures of political leaning, political interest, and policy issues. They showed that Reddit users tend to have more centrist and normally distributed scores than the survey data, skewing estimates toward the conservative end of the spectrum on all attitude measures. Another study, from Pasek et al. (2020), explained that SMD might be better conceived as providing insights about public attention rather than (“survey like”) attitudes or opinions. To do so, the authors compared tweets mentioning the presidential candidates and open-ended survey questions about the candidates to assess whether spikes surrounding political events correlate between both data sources. Results display some support for the correlation between social media attention and survey data, but they also show systematic differences that need to be better understood to assess when SMD can best generate insights about select topics. The research comparing both data sources tends to remain focused on volume analysis and tonality assessment. This type of research also tends to pay little attention to the domain-specificity of the SMD collected as well as to ways of mitigating replicability and consistency issues (e.g. [ 34 ]). For instance, the evolution of search queries around a given theme might lack precision and consistency over time. The connotation of hashtags can change or whole hashtags can even disappear. Better combining both data sources also requires elaborating more sophisticated measures of opinion and attitudes. One could think about pushing forward “stance detection” in complement to “sentiment detection”, but also about advancing “narrative analysis” in complement to “topic or frame detection”. These are avenues where computational social research would benefit from the expertise of applied computational linguistics.

A fifth approach implicates using SMD to generate new insights. This is especially useful when survey data are not available or when survey data are not recent enough (n = 32, see Table 7 in Appendix). Here, the main purpose is to improve the interpretability of the research by adopting an “ethnographic” methodology. By avoiding rigid research design plans, SMD can remain responsive to, and pursue, new paths of discovery as they emerge. Based on the papers collected, we found typical reasons for relying on SMD to generate new insights, such as capturing emergent opinions, expanding the scope of survey measures, validating survey measures, proposing novel approaches to get a more nuanced or dynamic perspective on PO, and making causal analyses (see column “Reason to complement” in Table 6 in Appendix). When used for capturing emergent opinions, SMD allow us to study the topical and normative climate around specific issues for which we have no theoretically grounded ideas yet. In this exploratory design, social media can provide survey researchers with a snapshot of important societal and political concerns worth surveying in future research. This is especially useful for emerging topics, such as nuclear power (e.g. [ 50 ]) or health-related policies [ 65 , 74 ]. On these emerging issues, SMD can be used in an exploratory or ethnographic perspective to generate initial and qualitative insights into under-studied research objects in order to develop quantitative survey measurements. SMD can also be useful for expanding the scope of survey measures on topics that are difficult to survey. For instance, Hatipoğlu et al. [ 41 ] used SMD to study international relationships with a case study on Turkish sentiments towards Syrian refugees using Twitter. Another study by Guan et al. (2020) relied on the social media platform Weibo to study Chinese views of the United States. SMD can also be useful for validating survey measures. For instance, the study by Dahlberg et al. [ 20 ] investigated the meanings of democracy in a cross-country perspective to better understand differences in the usage of the term “democracy” across languages and countries. The authors’ findings aimed to inform survey measurements about the different conceptualisations of democracy, notably by highlighting translations and language equivalence issues in survey items. Another reason is to propose novel approaches for achieving a more nuanced or dynamic perspective on PO. For instance, researchers can add new components and improve “old findings”, which are difficult to measure with survey data. In this view, the study by Barberá et al. [ 7 ] modelled policy issue responsiveness using Twitter data, thus going beyond the more static perspective on issue congruence offered by surveys. In another study, Clark et al. [ 16 ] investigated organisational legitimacy in a case study about public reactions on social media to the Supreme Court’s same-sex marriage cases. The authors argued that SMD can lessen some of the limitations of survey research in the field, notably by accessing not just policy positioning among individuals but also a variety of features of political discourse, such as opinion intensity and emotions like anger or happiness. SMD can also be used to make causal inferences in order to understand changes in opinion before and after an event, such as measuring the effect of a promulgated law on PO [ 1 ]. Here, SMD allow researchers to rely on spontaneous opinions expressed online rather than on retrospective survey questions, and this can help develop policy initiatives. For instance, Tavoschi et al. [ 73 ] used Twitter as a “sentinel system” to assess the orientation of PO in relation to vaccination. Despite the advantages of SMD in providing new research insights, these studies tend to lack a rigorous contextualisation of the findings derived from SMD. In this respect, a reliance on SMD would benefit from implementing sequential designs, where social media help to identify specific populations or sub-topics, which could then lead to a second quantitative survey phase. Whenever possible, SMD would further benefit from a comparison with longitudinal surveys to assess the extent to which both data sources reveal similar dynamics of change. Future studies could further exploit SMD’s ability to generate new insights for research in sensitive fields, such as war, racism, sexual orientation, and religious beliefs. These are often topics on which it remains difficult to collect survey data, notably because of the social desirability bias (e.g. [ 52 ]) and the like (e.g. extreme response style, moderacy bias, and acquiescence), but also because of the fear of being denounced or because the topic is controversial.

The last approach using SMD and survey data complementarily focuses on using social media to recruit survey respondents. However, in comparison with the previous approach, the studies collected here usually analyse SMD and survey data in sequential phases. As we only consider papers that are in some way also related to PO and are not solely about recruitment of survey respondents and their socio-demographic characteristics, the number of studies we were able to analyse is much smaller (n = 8, see Table 8 in the Appendix). Our review demonstrates that the papers essentially tackle the problem surveys have in recruiting specific politically involved sub-groups of the population. In particular, the research relies on social media to access representative samples of social media users, for instance, those who commented on their countries’ elections (see [ 9 , 12 ]) or who posted at least one election-related tweet [ 79 ]. Furthermore, in these studies, ethical concerns (e.g. privacy, tracking, etc.), but also the technical affordability of the social media platform used, are discussed. The latter issue is important, as each social media platform has particular arrangements which are likely to influence the group of individuals that can be reached. Overall, future studies could think about extending the recruitment approach to enhance our knowledge of reactions to systematic events, topics, or other repetitive features (such as supporting an issue or taking part in actions), while eliminating recall errors. Furthermore, relying on SMD can help researchers pre-test their hypotheses for future surveys by uncovering relevant underlying discursive patterns or by making smaller-scale qualitative observations.

5 Summary and concluding remarks

The aim of this article was to provide a review of published papers on the complementarity of SMD and survey data for PO research. We started this review by situating our work within theoretical advances concerning the complementarity of both data source. There has been extensive work underlying the opportunities and (quality) challenges of SMD for answering social research questions. However, research attention has only recently turned to SMD as a source of expression of PO and of its measurement. Consequently, there is a need for more research to uncover the ways in which SMD can be best used for fostering the understanding of PO.

The main contribution of our review is to provide a complete picture of the empirical research on the topic while calling attention to the pros and cons of each approach and possible future paths of advancements. Though this review might not be exhaustive, it has enabled us to show six major complementarity approaches which were identified as responding to four different research purposes. Below we highlight the main research paths for each approach. Using both data sources complementarily for prediction purposes was by far the most prominent approach and it remains a research area which raises many questions about the potential generalisability of the findings, namely in terms of the representativeness and validity of social media measurements of PO. We believe that the most important difficulty lies perhaps in the manner in which these studies deduce political opinions or attitudes from SMD. Survey researchers readily admit that opinions are more difficult to measure than behaviour because they involve what people think and not just how they act. Thereby, the choice to rely on sentiment analysis or merely on volume metrics (such as the number of retweets or mentions) seems unclear, at least for the near future.

Approaches concerned with improving sustainability have a significant potential for advancing social research, as they allow researchers to combine the richness of SMD content with established survey measures. When SMD are used in similar contexts to survey data, we believe that a critical view should prevail, informed by current social science best practices and expertise. For instance, whereas surveys draw a sample of carefully worded and standardised questions, social media can cover many topics as well as different facets of the same topic, which are not necessarily defined a priori on a theoretical basis. This research avenue is most likely to be fruitful for studies aiming to augment surveys by mapping discussions that are topical on social media, while allowing variations at country or regional levels of analysis to be discerned (e.g. Bennett et al. [ 10 ] on climate change opinions). Studies aiming to compare both data sources are certainly the most suitable to help improve our understanding about when and how both data sources can be validly combined. Survey methodologists can play a decisive role, notably by paying attention to the type of (open-ended) questions that can be more directly comparable with SMD. This direction can also inform the lack of consistent evidence for the first prediction approach.

Alternatively, studies aiming to improve reliability see research as mostly requiring control for the still severe limitations of using SMD appropriately in a PO context. In this respect, studies enriching survey data with SMD offer a solution to the fact that social media often lack relevant individual information, such as respondent’s attributes (e.g. sociodemographic characteristics or personality traits) or key outcome variables (e.g. voting, social, or political attitudes). Additionally, the “survey as proxy” approach enables researchers to calibrate SMD according to standardized survey measures at the actor (e.g. political candidates or parties) or context levels by reversing the data linking strategy. Future paths for both approaches implicate opening up the analysis to non-individual levels.

Studies aiming to improve the interpretability of survey research by generating new insights or by recruiting respondents on social media for a second survey phase, and that use both data sources complementarily, offer additional fertile ways to consider for new analyses that would not be possible using survey data alone. In this view, SMD do not aim to replace opinion surveys, but aim to provide a broader context for interpreting opinion, which will then serve to improve the quality of survey questions. This research avenue is most likely to be useful for knowing more about hard-to-reach populations (e.g. the LGBTQI* or disabled persons communities) or topics that are difficult to survey (e.g. violence and racism), especially when conducting iterative phases of analysis. It is also useful to get “opinion climates” about topics which have long been under survey scrutiny (e.g. emerging concerns related to feminism or social inclusion) in order to develop “updated” survey measurements.

Bringing together the opportunities offered by these different approaches shows that samples of social media users do not necessarily have to be representative of the general public to be used meaningfully as a complement to surveys. Most importantly, we believe that SMD should supplement, but not replace, traditional methods and data sources in the study of PO. By keeping up with current developments, we believe that remaining in the framework of survey research when using both data sources complementarily is paramount for identifying potential non-survey data sources, accessing them, and assessing their quality and usefulness for the study of PO. Like mixed-method approaches combining qualitative and quantitative data (e.g. [ 36 ]), the primary motive for complementing survey and SMD with one another is to allow researchers to mix datasets in a meaningful way for developing an overall interpretation.

5.1 Technical and ethical note

Regarding sustainability, it is important to consider that the patterns of social media consumption are influenced not only by user preferences, but also by technological changes and the availability of the platforms. For instance, social media companies may not survive and whole platforms could disappear, thus impeding data access. With changes in consumption patterns, PO may be difficult to measure consistently over time. From a more technical perspective, it is also important to assess the extent to which databases composed of social media texts collected by different means (e.g. different search queries or different platform algorithms) might raise consistency and replicability issues (e.g. [ 34 ]). As for reliability, several issues are worth considering. Even though SMD can provide complementary information to survey estimates though linkage, there are sometimes concerns about the veracity or honesty of the information collected. For instance, SMD may increase the potential for social stigmatisation, causing users to be more reluctant to share their true opinions [ 63 ]. However, the opposite may also be true: users could express more radical opinions to gain social approval (e.g. disinhibition effect). The identity of those who post can also raise veracity concerns [ 55 ], and it may be difficult to distinguish sarcastic content from texts that are straight-forwardly positive or negative (e.g. [ 35 ]). Another important issue is that we usually know how many people have liked a post, clicked on a link, or retweeted a message, but we rarely know how many people have seen the item and chosen not to take any action [ 77 ]. Furthermore, due to algorithms that favour selective exposure and homophily of opinion [ 6 , 17 ], it is important to assess the extent to which findings derived from online opinion generate more polarised opinions than the ones that would be obtained through the private setting of surveys.

When researchers aim to generate new insights, they should consider that each social media platform has particular arrangements. For instance, the orientation of the content (e.g. political, family-oriented, business-oriented) as well as the scope of the content (e.g. possible bias toward more visible events) can play a decisive role on what content is available and which user profiles are most likely to be active on the social media platform. Furthermore, the nature of the platform allows for different levels of engagement in debates (e.g. Twitter is mostly used for short text content, while YouTube and Instagram allow sharing and commenting on videos and pictures). Functional capabilities can not only influence the ways of recruiting respondents for a second survey phase (e.g. direct messages), but also the identifying of sub-groups of interest (e.g. differences between friend and follower networks, and the reciprocity of follower networks). In addition, social media platforms may give users control over the availability of the information (e.g. to suppress or filter unwanted comments), which will again impact what is available from whom and on what.

For each research purpose, we should also consider that there are important ethical factors that are likely to influence the possible paths of research relying on SMD. Each platform has its own rules which are subject to change at any time. For instance, anonymity settings also affect the content of SMD, with growing concerns about surveillance and the resulting loss of privacy [ 29 , 76 , 78 ], thus influencing what people are willing to post. There are also evolving rules about the banning of particular words and behaviours, as well as users, which may influence research findings (especially when conducting longitudinal research). SMD are private property of tech companies and can be arbitrarily erased or made inaccessible, compromising the replicability of research.

5.2 Outlook

Our review has several limitations. First, it focuses on social media but do not include other data sources that are frequently compared to survey data to model PO (e.g. Google trends, mainstream media, or administrative data). We thus encourage future research to extend the proposed complementary framework to additional data sources. This would allow the building of knowledge about the most suitable ways of combining these data for answering specific research purposes. Furthermore, our review entails a conceptual aim with less focus on the variety of methods used to either collect, clean, analyse, and aggregate the data to generate statistics. Discussing the pros and cons of methodologies employed by these papers could constitute the object of another review.

Notwithstanding these limitations, our study is not only of interest for social and political scientists concerned by the declining response rates and restrictive budgeting for survey research [ 57 ]. As social media have been established as multifunctional tools, and many companies and researchers implement strategies based on social media to collect opinions, make predictions, study behaviours, conduct experiments, or recruit hard-to-reach populations, this review is also of interest for practitioners.

Extracting PO from social media text can foster social sciences by moving it forward as an applied field, thus bridging gaps between computational models and interpretative research. We see this collaboration as particularly important for developing more advanced and reliable measures of opinion from social media texts. This also constitutes an opportunity to challenge the opposition of the so-called data-driven and theory-driven approaches , a simplistic dichotomy which further consolidates the misconception that social research can be conducted by relying solely on text-based data. We encourage researchers to acknowledge the different conceptualisation of opinion when measured by SMD and surveys, and we advise them to adopt a mixed-method strategy where the complementarity of both data is paramount.

Data availability

Please refer to the appendix.

Adams-Cohen NJ (2020) Policy change and public opinion: measuring shifting political sentiment with social media data. Am Politics Res 48(5):612–621. https://doi.org/10.1177/1532673X20920263

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Impact of COVID-19 on the psychological and behavioral health of college students worldwide: a knowledge mapping approach

• Jian Li 1   na1 ,
• Eryong Xue 2   na1 ,
• Biyun Liu 2 &
• Qing Han 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1353 ( 2024 ) Cite this article

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The outbreak of COVID-19 had a significant impact on the psychological and behavioral health of college students. However, few studies have systematically explored the relationship between COVID-19 and psychological and behavioral health among college students worldwide. Therefore, the purpose of this study was to explore the impact of COVID-19 on college students’ psychological and behavioral health using a knowledge-mapping approach. In total, 796 publications were selected and analyzed to clarify the publication volume and time distribution, core authors, major journals, research institutions, country distributions, research hotspots, and core themes. Since the outbreak of the COVID-19 pandemic in 2019, studies focused on the impact of COVID-19 on college students’ psychological and behavioral health showed an increasing trend year by year. The three countries with the highest centrality were Britain (0.34), the United States (0.24), and Mexico (0.13). The five major topics of research were mental health, academic pressure, physical health risks, college students’ majors, and daily living habits, with most research concerned with college students’ mental health. The visualized burst detection results were combined to identify three cutting-edge research topics in this field: the sustained impact of COVID-19 on college students’ mental health, the sustained impact of COVID-19 on medical college students, and the mediating role of college students’ mental resilience during COVID-19. We conclude by discussing the implications of our findings.

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Introduction.

The outbreak of the COVID-19 pandemic created a huge shock across the world and profoundly affected all aspects of society, including education. The pandemic had a significant impact on the psychological and behavioral health of college students. Many previous studies investigated the impact of the pandemic, and a common aim was to provide necessary psychological and behavioral guidance for college students who were negatively affected by the pandemic. COVID-19 has brought many lifestyle changes for college students, including changes in time spent on electronic devices, the number of private meetings, monthly drinking, meal deliveries, outdoor activities, late-night and daily snacks, and daily coffee intake; these changes had different levels of impact on college student’s mental health (Lee et al., 2022 ). The pandemic also disrupted normal teaching at universities, which posed major challenges for higher education. Furthermore, the requirements for social distancing created a surge in Internet use, given students’ demand for social interaction. In addition, the chain of “online social support → self-esteem” deeply affected the amount of loneliness suffered by college students when they were unable to change their real-life situation in the context of pandemic restrictions (Luo et al., 2022 ). The pandemic itself was an additional stressor, which potentially increased the risk for mental disorders among college students, thereby further altering their lifestyles and compromising their mental health (Buizza et al., 2022 ). As a vulnerable group, college students were also at high risk for depression and suicide attributable to the outbreak. Interestingly, college students who did not have lifelong mental health disorders were at greater risk for planning suicide than college students with these disorders. Therefore, research and interventions with longer follow-up periods are required to clarify how college students should respond to such a pandemic to reduce the occurrence of these extreme behaviors (Borges et al., 2023 ).

Extensive studies were conducted during the pandemic on the impact on the mental and behavioral health of college students. However, there are few studies explored the relationship between COVID-19 and the mental and behavioral health of college students worldwide. Therefore, this study examined the impact of COVID-19 on college students’ psychological and behavioral health using a knowledge-mapping approach. We used CiteSpace software to conduct a knowledge graph visualization analysis of the literature related to the impact of COVID-19 on college students’ psychological and behavioral health. We focused on the Web of Science database and objectively analyzed the major issues and development trends in this field, providing corresponding suggestions to support the improvement of college students’ psychological and behavioral health after the pandemic.

The significance and necessity of exploring the impact of COVID-19 on the psychological and behavioral health of college students on a global scale

It is significant and necessary to conduct studies regarding the impact of the pandemic on the psychological and behavioral health of college students worldwide (Borges et al., 2023 ; Lee et al., 2022 ; Gibbons, 2022 ). Current studies have highlighted that the impact of the pandemic on the psychological and behavioral health of college students is a challenging issue globally (Abdeahad and Mock, 2023 ). For example, based on a survey data sample of 30,383 students in 62 countries, the largest and most comprehensive study on college students’ perception of the impact of the first wave of the pandemic crisis on different aspects of their lives has been carried out so far. This study covered multiple types of countries and regions, as well as different types of academic institutions, such as European and American countries. Samples were collected from the United States, Germany, Spain, Switzerland, Asian countries, China, India, Saudi Arabia, Vietnam, and a few other countries in Africa. It is shown that the satisfaction of college students with certain social demographic characteristics, such as gender, type of university, grade, economic problems, and so on, is different. A set of recommendations should be developed for national policymakers and higher education institutions to support students in navigating the crisis caused by this outbreak and in possible future pandemic crises (Aristovnik et al., 2020 ).

Although the immediate effect of the pandemic has weakened, the great changes in the psychological and behavioral patterns of college students brought about by the pandemic have left an indelible lag effect (Rohde et al., 2023 ). For example, this influence can be a positive change in the online learning model and bring about innovative changes in education. While due to the constant changes in learning patterns during the pandemic, college students must endure a higher risk of mental health and stress, and behaviors related to student health further deteriorate. Of course, quality of life scores on mental health do not fully account for the stress levels of online college students, and the impact of online learning on the perceived stress levels of college students needs further research (Chusak et al., 2022 ). It can be the strengthening of physical fitness brought about by the increase of positive forms of home exercise and campus recreational sports (CRS), the improvement of psychological quality, and further development of self-expansion brought about by the improvement of resilience to cope with major crises (Halat et al., 2022 ; Abdeahad and Mock, 2023 ). For instance, it can be the subversion of negative eating and sleeping habits, behavioral disorders stemming from excessive electronic addiction, and psychological problems arising from mental breakdown caused by great challenges in life, study, and work (Chusak et al., 2022 ). The spread of the COVID-19 disease has restricted many normal social life, and strict risk control will threaten people’s eating habits and mental health, and susceptible college students may show more prominent eating disorders and mental health problems (Wu et al., 2023 ). For college students who have a certain anxiety tendency in study and life, defensive pessimism and optimism are effective in stimulating learning motivation. Further development of situational control, support, and strategies related to student personality during the pandemic can enhance students’ resilience (Gibbons, 2022 ).

Therefore, based on long-term consideration rather than limited to the present, it is of great significance to explore different lessons from the pandemic and carry out in-depth research to face various possible major global crises and challenges for a global scale.

Impact of COVID-19 on college students’ psychological and behavioral health worldwide

Many studies were conducted during the pandemic to explore the impact on contemporary college students. Now that social norms have been largely restored after the height of the pandemic, college students, whose lives and studies were greatly affected during the COVID-19, have been able to continue their study on campus, graduate, and embark on careers or further study, or have already switched to the identity of social workers.

Some studies used fear appeal theory and social learning theory to explore the impact of perceived threats on psychological anxiety among college students in China at the beginning of the COVID-19 pandemic and to clarify the intermediary role of reaction efficacy and self-efficacy (Zhang et al., 2022 ). Some studies used questionnaires with different scales, multiple regression models, and hierarchical analysis methods and revealed that many Chinese college students had serious mobile phone addictions during the pandemic, which were related to depression, anxiety, and insomnia. It has been found that online learning exacerbates problematic smartphone use and mental health problems, providing valuable information for targeted psychological interventions in the post-pandemic era. A study that followed different groups of college students and used generalized estimation equation models to estimate the effects of preventive behaviors and mental resilience on mental health during the pandemic found the prevalence of depression had increased at follow-up, and that of anxiety and stress had decreased (Li et al., 2023 ). Other studies obtained information from students using snowball sampling and cross-sectional survey designs and concluded that the positive impact on psychological well-being may help students adapt to other negative impacts during the pandemic and alleviate the pressure on emotional well-being (Mishra and Kumar, 2023 ).

It was found that the pandemic had a greater negative impact on the health behavior of students in European countries and the United States compared with Asian countries, which may reflect differences in the time course of the pandemic and the number of cases (Du et al., 2021 ). One study compared Chinese college students in China and South Korea with their knowledge during COVID-19, pandemic defense behavior, and mental depression, and explored the key factors that contributed to these students’ depression. The study found that students living in South Korea performed better in terms of preventive behavior but had a higher rate of severe depression than the mainland group. These conclusions can provide a reference for further research in different regions on different measures to reduce depressive symptoms in college students. (e.g., psychological counseling and physical activity encouragement) (Zhao et al., 2021 ). Another study used an online survey during the pandemic period to investigate differences among international college students in China, including gender-based differences (Li et al., 2021 ). In addition, a study interviewed LGBTQ college students and found that about 40% of them were not satisfied with their lives at the beginning of the pandemic, and almost all of them were worried about the threat of the coronavirus to their mental health. Some participants also feared seeking care during the pandemic because of their LGBTQ identity (Gonzales et al., 2023 ). That study concluded that there were significant differences in psychological distress and coping strategies among different groups. However, other studies have found no significant differences in the psychological impact of the pandemic among students of different ethnicities (domestic and international), genders, and learning levels (Yassin et al., 2021 ). A study that investigated different professional groups reported that pharmacy students showed depression, anxiety, stress, and low mental resilience 1 year after the outbreak of the pandemic (Halat et al., 2022 ). That study suggested it was necessary to investigate the long-term psychological impact of the pandemic on college students (Rohde et al., 2023 ).

At the national level, different countries have different policies and technical support for COVID-19 response, so the emotional responses of college students are also different (Gonzales et al., 2023 ). This shift in learning patterns can also lead to problems related to anxiety and mental health among students (Korneeva et al., 2022 ). For example, a qualitative study, that explored the impact on the mental health of young people in Jakarta, Indonesia, after a year and a half of isolation during the COVID-19 pandemic, provided important insights into the well-being of Indonesian youth following extended social restrictions during this period (Rahiem et al., 2021 ; Xiao, 2021 ). By studying the coping strategies of college students at the Polish Sports University during the second wave of COVID-19, it was found that the coping strategies of acceptance, positive coping, physical activity, and positive restructuring were most used (Guszkowska and Dabrowska-Zimakowska, 2022 ). Focusing on the relationship between the COVID-19 pandemic and the academic performance and health of South Asian students, it was found that South Asian students face additional challenges, including a worsening academic experience in higher education, increased mental health, the malignant spread of misinformation and an increase in religious tensions. South Asian students have a unique experience in higher education in California, and they often must deal with higher pressures to fulfill the various social responsibilities of being first, second, or third-generation Americans (Quraishi, 2023 ). Religion has also become the focus of research scholars. In Saudi Arabia, due to the influence of religion, strict social norms restrict women’s social gatherings and outdoor sports, etc., so it is necessary to explore the mental health symptoms of depression and the development of preventive behaviors against the pandemic in Saudi Arabian college students from a religious gender perspective (Aldhmadi et al., 2021 ; Edara et al., 2021 ).

At the institutional level, the university environment has a potential role as a target for implementing interventions to promote learning progress, build healthy study habits, and develop well-being among students. The pandemic created additional challenges for universities in terms of supporting students’ study habits (Clarke et al., 2021 ; Xue et al., 2023 ; Zhou and Zhang, 2021 ; Xu et al., 2021 ). Comprehensive mental health services and targeted suicide prevention initiatives were therefore critical for college students during the pandemic (Xu et al., 2021 ). Physical activity was also important, as it could effectively alleviate the adverse mental health effects brought about by the pandemic. Supporting and encouraging certain groups (e.g., senior students and rural college students) to participate in a certain level of physical activity may improve their subjective well-being and help them to cope with the adverse effects of the pandemic (Yuan and You, 2022 ; Zhang et al., 2022 ). During this period, psychological problems were common among college students, especially among those who were younger, had lower grades, often skipped breakfast, had poor quality of sleep, had sluggish state of learning, and had poor dormitory relationships. Under the situation of COVID-19 containment and normalized management, college students should form good living habits to effectively promote mental health, such as eating breakfast on time, exercising regularly, going to bed early, maintaining a good relationship with roommates, participating in non-congregate interpersonal activities in a small area, and taking the initiative to seek psychological help (Xu et al., 2022 ).

At the individual level, being isolated for observation or treatment, death of a family member or friend due to COVID-19, seeking help from others rarely or never, low support from relatives or friends, low support from family members, poor relationships with parents at home, more time spent on electronic devices in addition to daily online learning each day, and anxiety about going back to school were risk factors for depressive symptoms among college students during the pandemic. Academic pressure and fear of the pandemic were the main causes of anxiety (Yu et al., 2021 ). A study involving college students attending elite Italian universities found that during the pandemic and shift of teaching to distance learning systems, college students experienced more anxiety from interference with interpersonal relationships and academic demands. However, being surrounded by supportive relationships and the motivation to cultivate personal interests reduced anxiety (Nola et al., 2023 ). The pandemic has limited a lot of self-care activities, including a wide range of social interactions; however, college students could potentially buffer loneliness in their busy and stressful schedules, both during and after the pandemic, by strategically prioritizing people and activities that were more likely lead to generating meaningful social interactions. Meaningful social interaction is a self-care strategy that can help improve mental health outcomes and alleviate loneliness among college students (Barankevich and Loebach, 2022 ).

Previous studies presented comprehensive characteristics in terms of research comparisons. The first main characteristic was the combination of multiple research methods and considering the differences in research results under different research methods. Using a hybrid design approach, researchers examined the behavioral and psychological changes among students at a large national university in Australia during the pandemic in 2020 and at the end of the academic year 6 months later (Nicholson et al., 2023 ). The quantitative data showed that students’ learning attitudes were poor during the pandemic, but the qualitative data found students’ attitudes toward online learning were both positive and negative. Students’ mental health was relatively poor at both study time points, and the format of online learning had a negative impact on their learning immersion and psychological health, reflecting universities need to prioritize students’ psychological health while also prioritizing the continued development of their academic skills (Nicholson et al., 2023 ). The second approach was to conduct comparative studies with multi-national and multi-gender participants in different timelines to compare potential cultural and gender differences (Wang et al., 2023 ). The third approach comprehensively considered the common influence of psychology and behavior and provided all-round suggestions for college students’ health. Some scholars provided vital baseline data when studying the behavioral health and mental health of college students in ASEAN during the pandemic. With the pandemic over, and as students fully return to their academic institutions, colleges should pay extra attention to the healthy diet and physical exercise of college students. In addition, colleges should also carefully monitor mental health, which is still hotly discussed among college students. To effectively promote the health of universities, the existing action plan should be continuously updated so that college students in the ASEAN-7 countries can achieve long-term development (Rahman et al., 2022 ).

Research design and data sources

In this study, the Web of Science Core Collection database is used as the sample source database. During the search, this study followed the internationally common standardized literature selection and analysis process of Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) ( http://www.prisma-statement.org/ ). The whole process generally includes planning, literature search, literature evaluation, data extraction, data integration, and review writing. Because of its transparent and standardized research process, this method has gradually attracted the attention of social science research peers. According to the requirements of the research theme and research standardization, this study has set the criteria for the inclusion/inclusion of selected publications.

The inclusion and exclusion criteria

The search scope is limited to the title, abstract AND keywords in the database, and the Boolean logic operator “and” is used to connect the search keywords. The results are: (university OR college) AND (student*) AND (COVID-19 OR Corona Virus Disease 2019) AND (mental OR psychology* OR emotion*) AND (behav* OR learn*) AND (health), a preliminary total of 1314 articles were obtained. The aim was to ensure that the literature included research on the physical and mental health of college students in the context of the COVID-19 pandemic. If these conditions are included in it, they are included in the scope of the document.

In January 2020, Chinese scientists identified a novel coronavirus, namely the 2019 novel coronavirus (2019 CoV). On February 11, 2020, the World Health Organization (WHO) officially named this novel coronavirus SARS CoV-2 and the disease caused by it was called the 2019 coronavirus disease (COVID-19). At the same time, the other two coronaviruses, came into public view again, and the differences between SARS CoV-2 and them in biology, epidemiology, clinical diagnosis, and treatment also became a concern. The hotspot of. SARS-CoV-2 virus is a member of the coronavirus family. SARS-CoV-2 is the seventh coronavirus that can infect humans. It belongs to the coronavirus beta family, COVID-19. The disease caused by this virus is named COVID-19 infection, reflecting the heredity and similarity with the SARS coronavirus. Since the 2019 coronavirus disease is caused by SARS-CoV-2 virus infection, there is little literature supporting the close relationship between SARS-CoV-2 infection and the psychological health consequences of college students. On the contrary, many studies have shown that the lockdown measures taken to limit the spread of the virus after the outbreak of COVID-19 have had an impact on the mental disorders and symptoms, suicidal tendencies, and access to emergency mental services of college students. Therefore, this article attempts to discover the physical and mental health of college students after the outbreak of the pandemic, focusing on the period after the outbreak. Thus, the subject of the search formula finally determined by this study is COVID-19 OR Corona Virus Disease 2019.

Screening process

The time span is from January 2020 to October 2023. According to the above search conditions, the earliest published literature is March 2020, so the start time of screening is set as January 2020 in this paper. The last time the data was retrieved was October 19, 2023. The reason for this is that COVID-19 began at the end of December 2019, and relevant research has only gradually begun since then. On 31 January 2020, WHO officially defined the pneumonia outbreak due to novel coronavirus infection as a “PHEIC” (Public Health Emergency of International Concern). On 11 March, WHO considered that the current outbreak of novel coronavirus infection could be described as a global pandemic, while on 5 May 2023, WHO declared that the COVID-19 pandemic no longer constituted a PHEIC, but the organization would continue to coordinate the global response to the outbreak. So what we studied was the impact of COVID-19 on college students during this period. To further ensure that the literature conforms to the theme, the literature type is set as academic journal Article, Early Access, Review Article, and the language is set as English, and 1258 literatures are obtained. (1 article with inconsistent year, 21 articles with inconsistent language, and 34 articles with inconsistent document type were excluded).

To ensure compatibility with the research topic, manual screening was used to review the title, abstract, keywords, and other information of all literatures: first, if in the context of COVID-19, they were included; Secondly, the research object is college students, which is included; (The students included in the study included undergraduate students, master’s, and doctoral students.) Finally, the research topic of physical and mental health was included. After the first manual screening, 460 literatures that did not meet the theme were eliminated. To ensure the accuracy of the literature, the researchers conducted a secondary screening according to the above process, and then eliminated two literatures that did not meet the theme, and finally obtained 796 valid papers.

Research procedure

This study mainly used knowledge graphs and visualization methods to analyze the relevant literature. Mapping the knowledge domain produces an image that uses the knowledge domain as an object and shows the relationship between the development process and the structure of knowledge. It offers both a visual knowledge graph and a serialized knowledge lineage and has the dual characteristics of “graph” and “spectrum”. In graph form, it presents the network, structure, evolution, cross, and other hidden and complex relationships between knowledge; knowledge veins that are not easily noticed reflect the generation of new knowledge. We used CiteSpace6.1 to draw the knowledge map, and the relevant literature was quantitatively and qualitatively analyzed to explore the status quo, research hotspots, and research frontiers related to the continuous impact of the pandemic on college students’ psychological and behavioral health. The 796 selected studies were exported as text files, and CiteSpace6.1 software was used for data conversion. In this software, we set the time span to 2020–2023, and #Year per slice to 1 year. For node types, we selected author, institution, country, and keyword as analysis objects, and used the co-occurrence graph, cluster view, and time zone view to analyze the research progress on the continuous impact of the pandemic on college students’ psychological and behavioral health (Fig. 1 ).

A knowledge mapping flow chart of the impact of the pandemic on college students’ psychological and behavioral health.

Time distribution analysis

Examination of publication time showed that, since the outbreak of COVID-19 in December 2019, research on the impact of the pandemic on college students’ psychological and behavioral health showed an increasing trend year by year, but a decreasing trend in 2023. The number of published papers in 2020 was the lowest, at only 38 papers. This may be because the pandemic broke out globally at the end of 2019, and pandemic prevention and control began around the world. The impacts on people’s lives, work, and study had not yet emerged, resulting in relatively few relevant studies. The time spent in the home office and online learning increased, especially for college students enrolled in 2019 who had experienced 3 years of pandemic containment that started soon after they entered school, this means that most of their time was spent in online courses at home or on campus. As time progressed, the uncertainty caused by the pandemic had a continuous impact on college students’ psychological and behavioral health, and related research also increased. The number of studies peaked in 2022. As the virulence of the virus weakened, control conditions around the world began to relax. By the end of 2022, most countries had revoked pandemic control, people’s lives had returned to a pre-pandemic state, students had returned to school, and the impact of the pandemic was slowly decreasing; therefore, related research also decreased (Appendix 1 ).

Core author analysis

In total, 246 authors were identified, with the top four authors (not including the first and second authors) being Goncalves, Aurelie (four papers); Charbonnier, Elodie (four papers); and Hsiao and Pao Ying (three papers). The visualization map of the core authors of the reviewed literature showed that the connections between the authors were few and simple. This indicated that the connection density of the authors’ cooperative relationship network was low, the connection scale was small and scattered, and only some scholars had cooperated twice or more (e.g., Liu Jin, Ha Mengying, and Liu Zhen). The calculation formula of core authors using Price’s law is mp = 0.749√(npmax), where npmax is the number of papers published by the author with the largest number of publications during the statistical period, and mp is the minimum number of publications by the core author. The core author group is formed when the number of papers published by the core author is above mp, and the papers written by the core author reach 50% of all papers in the field. It showed npmax was 4 and mp was 1.5, which meant that the authors who had published more than two papers were the core authors in this research field. The statistical analysis showed that 10 authors had published more than two relevant papers and a total of 29 papers had been published, accounting for 3.6% of the sample literature. However, as this was far from 50% of the literature, a core group of authors in this research field had not yet formed (Table 1 and Appendix 2 ).

Analysis of major journals

The top 20 journals published a total of 561 relevant papers, which accounted for 70% of all identified papers. The journals with the highest number of publications were the International Journal of Environmental Research and Public Health (178 articles), Psychiatry Research (121 articles), and PLOS One (91 articles). These publications mainly covered public health, mental illness, emotional disorders, medicine, and other research fields. The journal with the highest impact factor was The Lancet, which had an impact factor of 168.9 in 2022, making it one of the top four journals in the medical field. This showed that the academic quality and influence of studies on the impact of the COVID-19 pandemic on college students’ psychological and behavioral health had been recognized by authoritative international journals. The centrality of multiple journals in the journal co-occurrence graph was high, with the Journal of Affective Disorders having the highest centrality (0.08). Strong centrality journals were closely connected, indicating that there were many cases in which these journals appeared in the same literature at the same time (Table 2 and Appendices 3 and 4 ).

Research institution analysis

Analysis of the distribution of core research institutions can reflect the research status of college student’s mental health and behavior in a particular field, and the corresponding strength and academic influence of the research team can be further reflected through statistics showing the number of published papers from each research institution. Twenty institutions published 98 core articles, accounting for 13% of all relevant literature. Chinese universities accounted for 50% of these institutions, indicating that China paid more attention to research on the impact of COVID-19 on college students’ psychological and behavioral health, with Fordham University, Huazhong University of Science and Technology, and Sichuan University ranked as the top three. Among these institutions, Huazhong University of Science and Technology has a major academic influence on clinical medical research. It is in Wuhan, which had the earliest outbreak points of the COVID-19 pandemic in China; therefore, this institution had a deep concern about the impact of the pandemic, and there were many related studies. The co-presence chart of research institutions showed that the centrality of several research institutions was high, among which Beijing Normal University had the highest centrality (0.02). The number of papers published by Beijing Normal University also ranked at the forefront, which indicated that Beijing Normal University, as the national leader in education and psychology, paid great attention to college students’ psychological and behavioral health and had relatively rich research results (Appendix 4 ).

Country analysis

The analysis of the countries that issued publications reflected the attention paid by different countries to pandemic prevention and control and the development of college students in the field of higher education. We found that research in this field was conducted in 93 different countries. The ranking of the top 20 countries is shown in Table 2 . The top three countries were the United States (215 articles), China (167 articles), and the United Kingdom (49 articles). The three countries with the highest centrality were the United Kingdom (0.34), the United States (0.24), and Mexico (0.13), which showed that a core group of countries had formed in this field, and the countries at the center of public opinion during the pandemic also included these countries. Different countries adopted different modes of fighting the pandemic; for example, the United States focused on “herd immunity,” the United Kingdom tended to “co-exist with the virus,” and China adopted a “zero elimination” approach of strict prevention and control. Different anti-pandemic measures also showed the differences in different countries’ systems and had an important impact on the economic development of that country and the healthy lifestyles of the population. In the context of the pandemic environment, national research on the impact of the pandemic was conducive to promoting the respective countries to implement effective response and management measures (Appendix 5 ).

There are some potential reasons and implicit contexts for exploring why and how the United Kingdom, the United States, and Mexico are the countries with the highest concentration in this area of research. For example, during the COVID-19 period in the UK, the degree of policy tightness has continued to repeat, and the overall prevention and control measures are gradually relaxed. The number of British adults vaccinated against the new coronavirus is among the highest in the world, but active vaccination cannot completely protect against the new strain after mutation, so the British people gradually break the prevention and control policy has begun to “coexist with the virus” (Samuolis et al., 2023 ). At the same time, in the process of fighting the novel coronavirus, the British economy has suffered a huge challenge. In the context of “Brexit”, especially under the impact of the COVID-19, Britain’s economic recovery has always lagged behind other large economies. The adverse effects of the new coronavirus and the difficult rebound of the economy have a very serious impact on the normal life of the British people. How to make production, life, and learning gradually get on the right track in such an environment is an urgent issue for researchers to explore. As the world’s largest economy, the United States has the most advanced medical technology and the most powerful medical system (Borges et al., 2023 ; Buizza et al., 2022 ).

Since the outbreak, the data from the Coronavirus Resource Center of Johns Hopkins University in the United States shows that the number of confirmed cases and deaths in the United States occupy the first place in the world, and the people’s livelihood has been greatly affected. The most important reason is the deformed medical system in the United States. The monopoly of big capital in the medical industry causes high medical costs in the United States. The defects in public health governance make the United States lack unified, timely, and effective response measures in the face of major pandemics, resulting in people’s doubts about the government. In the later period of COVID-19, under the guidance of the “herd immunity” prevention and control policy in the United States, COVID-19 had a more far-reaching impact on people’s lives, work, and study, so the research on this has become an urgent need for scholars to form effective policy planning. Mexico is geographically located in the southern part of North America, but is politically and culturally part of Latin America, and has the second largest population in the region, and is also the main source country of the 2009 H1N1 influenza, although it has experienced health management of previous influenza outbreaks (Samuolis et al. 2023 ). In addition, Mexico still faces problems such as insufficient investment in public health, backward public health infrastructure, and a loose health system, so livelihood protection has become the biggest risk in Mexico during the COVID-19 pandemic. As a typical country with health capacity in the region, there is abundant research on pandemic prevention and control in Mexico (von Keyserlingk et al., 2022 ).

Analysis of research hotspots

Keywords are an indispensable part of academic papers and offer a high level of generalization of the content of academic papers. Therefore, keyword co-word analysis can reveal the research hotspots in a particular field. In this study, the research topics reflected by the keywords with high centrality and word frequency were the research hotspots in this field. We imported the 796 filtered papers into CiteSpace software, selected “keyword” for the node type, set the time span to 2020–2023, and set the time slice to 1 year. A keyword co-occurrence graph (Fig. 2 ) was obtained after running the analysis. The more keywords appear, the larger the square in the picture; the font size is the embodiment of the centrality of keywords, and a larger font indicates stronger centrality. To present the research hotspots in this field more clearly and intuitively, data such as keyword word frequency and centrality were exported from the background of CiteSpace software, and the top 20 keywords with the highest frequency were sorted (Table 3 ). Keyword occurrence frequency and centrality are not necessarily positively correlated. The higher the keyword frequency, the more it occurs, and the research topic appears repeatedly. The higher the centrality of the keyword, the stronger the mediating effect, which indicates the keyword has a greater influence on other keywords.

Keyword co-occurrences map the impact of the pandemic on college students’ psychological and behavioral health.

The top five keywords were “mental health,” “college students,” “depression or sadness,” “stress,” and “anxiety.” As the topic of our analysis was “college students” and “mental health and behavior,” the search terms included these words, so it was necessary to remove the words “college students” and “mental health.” A research hotspot is indicated when the centrality of a keyword is above 0.1. A comprehensive consideration of the frequency and centrality of keywords in our study showed the main research hotspots in this field were psychological stress, behavioral disorders and mental disorders, and risk perception (Table 3 and Fig. 2 ).

Psychological stress

The COVID-19 introduced many stressors into college students’ daily and academic lives. Various studies explored whether learning stress among students increased after the pandemic and how individual and situational factors modulated this potential increase in stress. Based on longitudinal survey data for stress levels and self-regulation efficacy among students in a public university before and after the outbreak of the pandemic, a regression analysis showed that the level of learning-related stress generally increased after the pandemic outbreak. Students with self-efficacy reported a lower increase in stress in self-regulation than those without self-efficacy. A greater increase in stress was associated with higher levels of mental health impairment and less school time. To solve the stress problems of students, universities should provide students with resources with corresponding solutions, so that their self-psychological regulation and time management ability can be improved (von Keyserlingk et al., 2022 ). Another study examined stress and coping styles during a pandemic lockdown at a United States university campus and included a scale to assess coping strategies and perceived stress. The results of the study showed that the stress generated during the lockdown was related to negative coping strategies such as emotional denial and behavioral detachment. Stress was negatively correlated with positive coping strategies, such as acceptance, planning, and positive coping. Therefore, it was recommended that during the lockdown period, health education efforts should focus on stress screening for students, providing mental health services and coping skills-related information sessions to students, as well as providing virtual recreation and social opportunities (Samuolis et al., 2023 ).

Behavioral and mental disorders

“Disorder” has two different meanings in literature. One refers to behavioral disorders, such as sleep and eating disorders, and the other refers to various mental disorders, such as post-traumatic stress disorder (PTSD) and attention deficit hyperactivity disorder (ADHD). It has shown that periods of economic “pause” and quarantines are likely to lead to risky health behaviors, such as increased self-abuse, drinking and eating irregularly, smoking, drug use, and alcohol consumption. Although the impact of the pandemic on people with eating disorders remains unknown, it may have contributed to increased eating disorder symptoms (e.g., dietary restriction, overeating, emotional eating) (Fila-Witecka et al., 2021 ). A study focused on sleep problems among Polish college students during the pandemic and the relationship between the severity of insomnia symptoms and psychopathological symptoms, PTSD, and behavioral factors showed that more than half of the students had a certain form of sleep disorder and suggested that sleep problems may be widespread among college students. In addition, although symptoms of insomnia and the severity of sleep disorders were significantly associated with all studied variables, the direction of these associations remains to be determined (Fila-Witecka et al., 2022 ; Takeda et al., 2023 ).

Risk perception

Both the absolute risk on the surface and the perception of implied risk were the focus of research on the potential risks associated with the pandemic. COVID-19 increased the risk for disease in the superficial sense (physical and mental illness), and some studies used random-effects models to calculate the combined prevalence by conducting narrative reviews to identify risk factors during the pandemic. The main risk factors identified were female gender, early school or pre-clinical years, exposure to COVID-19, academic stress, history of mental or physical illness, financial hardship, fear of impaired education, online learning difficulties, fear of infection, loneliness, low physical activity, low social support, and problematic Internet or smartphone use. During COVID-19, there has been a significant increase in mental health issues and related risk factors, which requires guidance on mental health. These findings are crucial for universities and health authorities to identify students at mental health risk and provide corresponding intervention measures (Peng et al., 2023 ). Furthermore, people’s perception of risk affected their preventive behavior during the pandemic. A study focused on Chinese university students and analyzed their sub-types of risk perception in COVID-19, identified the characteristics of these sub-types, and investigated the potential profile and influencing factors of risk perception. The results showed that pandemic risk cognition among Chinese college students was not ideal and had significant group characteristics and heterogeneity. Universities and public health practitioners can identify potential sub-populations to provide a theoretical and empirical basis for implementing risk perception interventions during outbreaks (Gan and Fu, 2022 ). People’s perception of risk also affected their emotional state during the pandemic. It is also shown that the risk and time perception of college students are significantly correlated with their mental health. Therefore, in the event of a sudden public health emergency, it is important to closely monitor the mental health status of college students, promptly adjust their attitudes towards the present and future, and consider their risk perception ability, to improve their mental health level in times of crisis (Cao et al., 2021 ).

Core theme analysis

The keyword clustering function in CiteSpace software is based on keyword co-word analysis; the analysis object (frequency) is subject to a clustering statistical algorithm, which simplifies the complex co-word relationships between many objects into relatively clear relationships between several class groups. This means the collection of topics with high correlation in a certain time can be intuitively summarized to reveal thematic trends in the research field. Using keyword cluster analysis and the log-maximum-likelihood rate algorithm, we drew a clustering time diagram (Fig. 3 ) that included 17 clustering results. Based on the similarity of clustering centers, 17 clusters were divided into five core topics (Table 4 and Fig. 3 ).

Keyword clustering analysis can simplify the co-occurrence network relationships of keywords into relatively fewer clusters through clustering statistics. Using the LLR algorithm for clustering analysis and arranging keywords in chronological order to demonstrate their evolution, each cluster has a corresponding straight line, and the nodes on the line represent the main research content covered by the cluster. Based on this, it is further condensed into five core topic clusters.

Cluster one: Mental health

The keyword “mental health” had a frequency of 373. Similar research topics included “psychological tolerance” and “psychological adjustment,” which also had a high frequency. The CiteSpace cluster summary table showed that since the outbreak of COVID-19, scholars have paid continuous attention to the psychological health of university students, and research in the field of mental health showed a rapidly rising trend from 2020 to 2022. After 2023, although the overall number of publications decreased, the proportion of studies on mental health remained large. Scholars mainly focused on cross-sectional research examining college students’ psychological endurance, psychological resilience, and adjustment effect.

Cluster two: Academic stress

The word frequency and centrality of “stress,” “anxiety,” and “online learning” were all at a high level. The keyword time zone table showed that since the outbreak of COVID-19, all students were studying online at home, which caused anxiety and distress for students; therefore, research on academic stress among college students showed an increasing trend. Research conducted in this area mainly focused on college students’ study habits, online learning satisfaction, self-efficacy, and academic pressure in the context of the COVID-19 pandemic. In addition, research focused on college students’ teaching methods, online teaching quality, and online interaction quality during the COVID-19 pandemic.

Cluster three: Physical health risks

The frequency of both “physical activity” and “health risk” were high. As shown in the keyword clustering time graph, the outbreak of COVID-19 meant people could not go out for physical exercise. Therefore, the impact of COVID-19 on health became a hot topic for many scholars and included research on college students’ physical health status, sports activity plans, and similar topics.

Cluster four: The major of college students

Since the spread of COVID-19 disease, college students have been a key area of concern, although the impact of the pandemic on various majors varied, with more words related to “medical students.” In addition, the keywords displayed in the keyword clustering time graph involved research topics such as freshmen, non-autistic students, and sports majors.

Cluster five: Living habits

The research on living habits mainly focuses on the changes in college students’ lifestyles, eating habits, and weight during COVID-19. Comparative research methods are commonly used to test and analyze the lifestyle habits of college students from different countries. Relevant research has made a comparative study on the impact of China, Spain, Indonesia, the United States, and other countries on college students’ living habits during the COVID-19.

Cutting-edge research analytics

A research frontier can be described as a set of scientific issues discussed in a certain period based on burst articles. A research frontier can be identified based on an analysis of burst terms, with comprehensive judgments and detection in combination with the analysis of relevant cited documents. The visual burst detection results obtained using CiteSpace software (Fig. 4 ) showed 10 emergent keywords in the literature related to the impact of the COVID-19 pandemic on the psychological and behavioral health of college students from 2020 to 2022, all of which represented topics with increasing research trends. These topics included mental healthcare, mental resilience, happiness, psychological impact, and medical students (Fig. 4 ).

Citation Burst analysis that reflects active or cutting-edge research nodes. Keyword emergence refers to the high-frequency appearance of keywords in a published article within a short period of time. From the beginning of keyword emergence to the end of emergence, a red horizontal line is formed to indicate the importance and attention of the keyword in the research field. The longer the emergence length, the longer the duration of the keyword’s popularity and the stronger the research frontier.

Ongoing impact of COVID-19 on college student's mental health

The COVID-19 makes people pay more and more attention to the psychological health of the disadvantaged college students. It shows that the mental health of college students during COVID-19 is worse than that of other groups. (Kang et al., 2021 ; Lovell et al., 2015 ) Not all studies indicate that the mental health problems of college students have worsened during this period. Some studies have found that the mental health problems of college students are declining or stabilizing, which is exactly the opposite of the situation mentioned earlier. Carpinelli et al. ( 2021 ) showed that disabled students and students with special learning disabilities are more satisfied with remote teaching than normal students. Only 22% of disabled students expressed dissatisfaction with the teaching methods used due to difficulties, including those related to weak technological infrastructure. Ding et al.’s study showed that sedentary behavior, challenges of online learning, feelings of isolation, and concerns about COVID-19 infection led to poor psychological and overall health among college students, but the results showed that most respondents reported good overall health. Related studies have shown that providing face-to-face learning experiences at an accelerated pace without addressing the underlying causes of mental health issues may not necessarily have a positive impact on student’s mental health. In general, although the direct impact of COVID-19 on the deterioration of college student’s mental health has not been confirmed, it does have a negative impact on some college students to varying degrees.

The COVID-19 outbreak in 2019 caused deep and lasting psychological damage. Medical students were at high risk for psychiatric problems during the COVID-19 pandemic, possibly because of the high risk for infection, major lifestyle changes, severe restrictions, and disruption to education (Elmer et al., 2020 ). Research also showed high prevalence rates of depression, anxiety, and sleep disorders among medical students worldwide during the pandemic. These common psychological problems may lead to the abandonment of medical studies. The lockdown of medical research institutions during the COVID-19 pandemic and the new challenges facing global healthcare systems had a dramatic impact on the quantity and quality of medical education. Therefore, the COVID-19 pandemic impacted medical students’ academic performance, as they were faced with learning challenges involving clinical skills and practical aspects such as laboratories. During the pandemic, medical students faced a higher risk for COVID-19 infection than other majors, which introduced additional psychological pressure for these students. Medical students have close contact with patients and their families because of their practical learning needs and work requirements. However, most young medical students lacked clinical experience, and the possibility of contact with patients with COVID-19 and the risk for infection was significantly increased compared with students from other majors. In addition to the “new” pressures brought about by the pandemic, original pressures based on exams, experiments, papers, and workloads were exacerbated by the pandemic. Students preparing for employment and graduation theses were under a greater psychological burden, as social communication was somewhat limited, traditional learning processes were disrupted, completion of expected academic work was disrupted, and heavy clinical responsibilities became a source of anxiety for students. In general, medical students, as the “reserve army” of future medical teams, should receive more attention in such situations. Relevant research focused on the psychological problems among residents, graduate students, undergraduates, and nurses at different levels. The results suggested that the COVID-19 pandemic had different degrees of impact on the psychological state of medical students, with stress stemming from fear of disease, worry about the pandemic, and anxiety about studies. Affected students showed obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, fear, and high scores for psychotic factors. These psychological problems in medical students occurred not only during the outbreak period but also in the post-pandemic era. Medical universities should consider the students’ mental health and medical personnel during a pandemic situation, establish a prevention and treatment system for psychological problems, take effective measures to prevent the occurrence of psychological problems, identify problems early, and provide targeted psychological treatment.

Mediating role of college students’ mental resilience during COVID-19

Psychological resilience refers to an individual’s ability to recover from adversity, setbacks, and failures, and is the ability to adapt, regulate, and “bounce back” psychologically when facing difficulties. This ability is related to an individual’s physical and mental health, career success or failure, and happiness index. The strength of psychological resilience reflects a person’s ability to adapt psychologically and their perseverance and determination in the face of difficulties. Psychological resilience not only helps us overcome difficulties but also promotes the process of psychological recovery, making us stronger and more energetic. Therefore, psychological resilience plays an important role in college students’ response to the changes in COVID-19. It can help college students better cope with setbacks and difficulties, enhance their self-regulation ability, and restore their mental health. When facing difficulties in academic performance, interpersonal relationships, and future planning, psychological resilience can make them more optimistic, resilient, and proactive in coping, thereby better-solving problems. In addition, the level of psychological resilience can have varying degrees of impact on individuals and directly affect the degree of anxiety and depression. People with high psychological resilience can self-regulate and relieve stress when experiencing stress, while those with low psychological resilience are more likely to experience anxiety and depression symptoms due to their weaker ability to resist adversity. Li and Xie ( 2022 ) mentioned that relevant research has investigated the mediating role of psychological resilience. Psychological resilience plays a protective mediating role in mental health issues such as stress, depression, fatigue, and anxiety, indicating that psychological resilience is a key factor in understanding stress and predicting anxiety. However, when college students face enormous pressure, it may lead to a decrease in their original level of psychological resilience. Overall, the psychological resilience of college students can be an important direction for future research, and intervening in their psychological resilience can help alleviate the impact of sudden public health emergencies on their mental health.

The purpose of this study was to analyze the relevant literature on the impact of COVID-19 on university students’ mental and behavioral health and to understand the status, core topics, and future trends of this research field. Based on the findings, this study drew several conclusions as follows.

Research on the impact of COVID-19 on college students’ psychological and behavioral health is increasing. Since the outbreak of COVID-19 at the end of 2019, it has had a tremendous impact on all fields around the world, including universities, and disrupted people’s normal life order. Universities around the world have ceased offline teaching and are now using online teaching methods. The changes brought about by sudden public health emergencies and the emergence of various problems in online learning have brought additional pressure on the mental health of college students.

Research focused on the impact of COVID-19 on psychological and behavioral health among college students has not yet been fully formed. Although many research keywords were identified in our analysis, the centrality of keywords according to word frequency statistics was <0.1, which indicated that a core research topic in this research field had not yet been formed. After comprehensive consideration of the frequency and centrality of keywords, we identified three main research themes. First, we identified research on the psychological pressure on students caused by the pandemic. The outbreak of COVID-19 led to great changes in college student’s daily lives and studies, and comparative studies showed that students’ study-related stress levels generally increased after the outbreak. In addition, some studies examined college students’ stress coping styles and sleep quality. Second, we identified research on college students’ behavior and mental disorders caused by the pandemic. A prolonged period of home pandemic prevention and control meant people were unable to work and students could not go to school, which may have resulted in a series of health behaviors. Relevant studies showed that college students suffered from eating disorders, insomnia symptoms, and PTSD symptoms after the pandemic. Although no studies showed that the occurrence of these symptoms was directly related to the occurrence of the pandemic, the pandemic can be considered one of the stressors that caused these symptoms. Third, we identified research focused on college students’ perception of risk. Relevant studies showed that college students’ risk perception ability was significantly related to their mental health. Therefore, we should pay attention to and improve college students’ risk perception ability, which will help to improve their mental and behavioral health levels in public health emergencies (Borges et al., 2023 ; Buizza et al., 2022 ).

Core themes of the impact of COVID-19 on college students’ psychological and behavioral health were formed, including mental health, academic pressure, physical health risks, college students’ majors, and life habits. These five core themes covered different aspects of the COVID-19 pandemic’s impact on the mental and behavioral health of college students from 2020 to 2023.

Most studies show that COVID-19 has had different effects on college students’ mental health, mainly including stress, anxiety, and depression. For example, a survey of over 700,000 Chinese students (Ma et al., 2020 ) showed that nearly 45% of students have experienced mental health problems, with anxiety being the most common symptom. Not only in China but also in a multinational study, it was found that 61.3% of students felt they were in a high-stress state, followed closely by symptoms of depression (40.3%) and anxiety (30%). Among them, a university student in Texas, USA, had a high level of stress and anxiety of 71%, and British university students also had higher levels of anxiety and depression. Chen and Lucock studied 1173 undergraduate and graduate students at a United Kingdom university and found that more than 50% of respondents had anxiety and depression levels above clinical norms.

We found many studies focused on college students majoring in medicine and health education. A reason for this may be that medical students are future members of the medical team, and the COVID-19 pandemic impacted medical students’ professional identity and chances of burnout, especially as they need a lot of clinical practice to accumulate experience. During the pandemic period, the practical needs of this major could not be met, which caused anxiety problems related to the academic pressure and professional quality of medical students. Therefore, close attention should be paid to the career development of medical students in the post-pandemic era.

The inability to go out during the pandemic impacted college students’ health, lifestyle, and eating habits. Studies showed that long-term isolation at home could lead to changes in daily activities including unhealthy dietary lifestyles, such as intake of health supplements, decrease of physical activity, and increase of ST. In addition, lifestyle changes such as increased intake of sweetened beverages, increased use of healthcare products, irregular sleep rhythm, and dietary changes may disrupt the normal rhythm of life and increase mental health problems. Therefore, the COVID-19 pandemic had a broad impact on college students’ daily life behaviors. It is worth noting that maintaining regular sleeping and eating rhythms is crucial for physical health.

Research frontiers on the impact of COVID-19 on the psychological and behavioral health of college students were strengthened, including research on topics such as mental healthcare, mental resilience, happiness, psychological impact, and medical students (Borges et al., 2023 ; Buizza et al., 2022 ). This study identified two frontier topics. First, we identified the continuous impact of COVID-19 on the mental health of college students, which included the impact on their mental health before COVID-19, and the continuous impact on their mental health after the end of the pandemic and corresponding intervention measures. Further research is needed to explore the true impact of the COVID-19 pandemic more fully on college students’ well-being and mental health, for example, investigating the impact of COVID-19 on college dropout rates.

A survey by the Social Relations Committee of the World Health Organization shows that about 20% of adolescents worldwide suffer from varying degrees of mental health problems, with student loneliness being a global public issue. (World Health Organization, 2023 ). Previous studies mainly focused on the impact of COVID-19 on college students’ lives, studies, and work, such as growth pressure, online course learning, remote communication, etc. Therefore, in the post-pandemic era, we not only need to continue tracking these impacts but also need to closely monitor the loneliness of college students. More than half of higher education students in Finland report an increase in loneliness (Finnish Institute for Health and Welfare THL In Swedish: Institutet för hälsa och välfärd THL, 2021 ); Hemberg et al. ( 2024 ) mentioned in their research that college students who experienced loneliness before the COVID-19 pandemic felt lonelier, their sense of happiness declined and became more apathetic due to the increased time spent alone during the COVID-19 pandemic. The reason may be related to reduced communication with peers, concerns, and anxiety about the unknown. In the study of related influencing factors, it was found that the loneliness of college students is related to negative events such as depression and anxiety they have experienced before. (Fegert et al., 2020 ). However, not all online activities will have a negative impact on students. Hemberg et al. ( 2024 ) noted in their research that online interaction through social media can help people alleviate negative emotions such as loneliness, depression, or unhappiness. Domokos et al. ( 2020 ) also found that physical activity can help adolescents and young people with depression or low mood regain energy and happiness while exploring the experiences of college students.

It is necessary to conduct long-term tracking of the physical and mental health status of college students in the post-pandemic era. It can consistently provide sufficient social support for college students in need. Based on the main findings of this study, we believe that continuous attention to the physical and mental health of college students will help us cope with potential public health emergencies in the future, take proactive measures, and help college students establish more active and healthier physical and mental defense mechanisms. Related studies have shown that after experiencing a period of social loneliness, students find it difficult to reconnect with their peers, especially those who are particularly prone to depression. External support should be provided as most students tend to hide their feelings (European Commission, 2022 ). We should not assume that students will automatically return to their original state. (Wright et al., 2021 ). Based on current research, we suggest long-term tracking of the physical and mental health of college students in the post-pandemic era to advocate for a healthier and higher-quality learning environment globally.

We identified the continuous impact of the COVID-19 pandemic on medical college students. Relevant studies on this frontier topic showed that during the COVID-19 pandemic, the prevalence of depression, anxiety, and sleep disorders among medical students worldwide was high, with academic and employment pressure created by medical students’ inability to practice clinical skills because of lockdowns. This had a major impact on the quantity and quality of medical education (Borges et al., 2023 ). In addition, the spread of the novel coronavirus and the mortality rate negatively affected the professional identity of some medical students. Therefore, further research should consider medical students’ mental health problems, academic pressure, professional identity, and related aspects, timely detection of problems, and offer targeted interventions.

We identified the theme of mediating the psychological resilience of college students during the COVID-19 pandemic. This cutting-edge topic showed that students’ psychological resilience played an important role in their coping with stress, anxiety, and depression caused by health emergencies. Further research should focus on improving the psychological resilience of college students to ensure they have psychological support and help them more effectively cope with various adverse emotions.

Contribution of this study

This study contributed to analyzing the current literature on the impact of college students’ experiences during the COVID-19 pandemic on their psychological and behavioral health. It aimed to explore the impact of COVID-19 on college students’ psychological and behavioral health using a knowledge-mapping approach. It was found that the three countries with the highest centrality were Britain, the United States, and Mexico. In this study, ranking the Top 20 research institutions according to the number of papers issued, it was found that the number of papers issued by Chinese research institutions accounted for 50%, of which Huazhong University of Science and Technology, located in the city where the COVID-19 first broke out, ranked second on this topic, and by analyzing the countries of the sample literature, China ranked second. It shows that China is very concerned about the impact of COVID-19 on college students’ psychological and behavioral health and is committed to contributing its own strength to sudden global public health events. However, for Chinese studies on college students’ experiences during the COVID-19 pandemic, there are few papers published in English and it is the reason why COVID-19 was first identified in China and does not appear on the list of countries with the highest research concentration. In addition, both Chinese scholars and foreign scholars agree that COVID-19 has a negative impact on the psychological and behavioral health of college students and call for appropriate intervention and treatment for college students who have already had psychological and behavioral impacts.

The five major topics of research were mental health, academic pressure, physical health risks, college students’ majors, and daily living habits, with most research concerned with college students’ mental health. The visualized burst detection results were combined to identify two cutting-edge research topics in this field: the sustained impact of COVID-19 on college students’ mental health, and the mediating role of college students’ mental resilience during COVID-19. Although most studies show that COVID-19 has a strong impact on college students’ daily life, study, and work. During this period, they need to reduce their outings. College students respond to the government’s call to stay at home for long periods of time, and they can only obtain information through television news, online media, and various social media platforms. Continuous 24-h epidemic reporting, closed home isolation environments, and other factors can cause individuals to pay excessive attention to the epidemic. In addition, some negative news and rumors that are exaggerated just to attract attention are mixed in, which has a negative impact on the physical and mental health of college students. At present, normal social life before the epidemic is slowly recovering, which has caused some students to encounter difficulties when returning to social interaction. Therefore, in the post-pandemic era, as college students return to campus life, we need to have a clearer understanding of the risks posed by the pandemic to them, as well as other mental health and rehabilitation issues they may face. These all require further research.

Conclusion: key points of findings

This study found that the COVID-19 disease had a lot of impact on the behavior and psychology of college students, including the negative impact on the life and study of some college students as mentioned above, while relevant studies also showed that it had a positive impact on college students. During the COVID-19, college students spent more time at home. Hemberg et al. ( 2024 ) mentioned in their research that Some studies showed that this led to the decline of college students’ physical and mental health, while some college students said that they felt more happy and happy moments, and students who suffered loneliness or anxiety during the COVID-19 had a new understanding of themselves and experienced greater gratitude. Because the increase in solitude time allows them to have more time to discover the small beauty of life and to have a deeper thinking and experience of life. (Nilsson et al., 2006 ; Eriksson, 1987 ; Hemberg et al., 2024 ). At the same time, the COVID-19 has slowed down the pace of life of people. The COVID-19 has made the relationship between people and their families closer, mainly because people stay at home more than they can go out during the epidemic, which makes families the warmest haven for people. During the days of lockdown and isolation, people had to rely on the support and care of their family members to get through that difficult time together. This intimate relationship and emotional connection make people cherish and value their families more. In addition, during the pandemic, people began to pay more attention to mutual support and understanding, knowing how to care for and understand each other in times of tension, which further deepened the emotional bond between family members. The increase in family activities, such as cooking together, watching movies, playing games, etc., not only enriches the lives of family members, but also enhances the cohesion of the family. These experiences have made people realize the importance of family in a person’s life, and thus pay more attention to the harmony and happiness of the family. Although the COVID-19 pandemic has reduced the opportunities for college students to learn and interact in life, their relationships with friends and family may also become closer or more important.

Through the study on the impact of COVID-19 on the psychological and behavioral health of college students, this study draws the following important conclusions: First, governments and higher education institutions should pay attention to the impact of major public health events on the psychological and behavioral health of college students. College students in different countries around the world have been affected by the COVID-19 to varying degrees. Due to differences in economy, culture, religion, etc., the impact reflects certain heterogeneity. The impact of the COVID-19 on the psychological and behavioral health of college students is not only reflected in the COVID-19 period, but also in all aspects of future work, life, and study, with both positive and negative impacts. Whether the impact of the COVID-19 is an opportunity, or a challenge is still controversial, but we should learn from experience to take more timely and effective measures when facing major crises in the future.

Second, it is necessary to actively intervene with college students who are negatively affected by the COVID-19 disease. Firstly, by conducting active and effective psychological counseling activities for college students, we can promote their mental health growth, prevent and treat mental illnesses, and optimize their psychological qualities. Many universities have established psychological counseling centers one after another, adopting various methods to provide psychological counseling to college students, and carrying out targeted prevention and treatment of psychological problems and mental illnesses. Secondly, various forms of promotion and popularization of mental health and hygiene and epidemic prevention knowledge should be used. Physical health and mental health are interdependent and mutually transforming entities. The spread of the COVID-19 is not only closely related to the environmental health status, but also closely related to the health habits of each of us. Therefore, it is necessary to attach great importance to hygiene and epidemic prevention in daily life and correct unhealthy habits. In addition, establishing a psychological service mechanism coordinated by multiple entities such as government departments, unit groups, grassroots communities, and social organizations to provide professional psychological services and support is also very important for alleviating the psychological pressure of college students. We are currently unclear about the problems that college students face when resuming normal offline learning and social interaction. Therefore, tracking research is needed to understand the long-term impact of the COVID-19 on the mental health of college students and provide support for them to adapt to face-to-face learning and socializing.

Thirdly, the overall deterioration in the mental health of college students during the COVID-19 pandemic is a particularly important area of research. During the COVID-19 pandemic, college students don’t have much social contact, and it can be a challenge to return to a “normal” daily life. This study provides those who work with college students with more insight into how college students spend their special time, while helping them stay positive during future major public health events. Finally, this study can provide policymakers with better insights into how to support college students in the future and provide mechanisms to do so.

In the meanwhile, this study also helps universities to recognize the possible negative impact of COVID-19 on college students’ mental health. Colleges and universities should strengthen students’ psychological coping and mental health education, establish scientific methods to prevent negative emotions, and pay attention to the progress of research after the pandemic, which will also provide ideas for further research. Research on the impact of COVID-19 on the psychological and behavioral health of college students has attracted major attention and has been considered in most medical education journals. Relevant research focuses included online teaching, anxiety, mental health, physical health, and lifestyle (Rohde et al., 2023 ). The COVID-19 pandemic was both a challenge and an opportunity for college students and sounded the alarm for researchers. Under the challenge of COVID-19, online teaching developed rapidly, an anti-pandemic spirit was integrated into ideological and political education, and the teaching system was improved. However, it also reminded us that major health emergencies are highly unpredictable, occur at any time, and can have a huge impact on education. Therefore, we should take this opportunity to conduct in-depth research and discuss countermeasures to better deal with the normalization of the COVID-19 pandemic, the post-pandemic era, and other major emergencies that may occur in the future, so that the adverse impact on higher education is reduced.

Data availability

The datasets generated during and/or analyzed during the current study are available in https://doi.org/10.7910/DVN/5UWGUE , Harvard Dataverse, V1.

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Acknowledgements

This study is funded by 2021 National Social Science Foundation of Higher Education Ideological and Political Course Research (Key project) Ideological and Political Education System Construction System Mechanism Research in New Era (No. 21VSZ004).

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Li, J., Xue, E., Liu, B. et al. Impact of COVID-19 on the psychological and behavioral health of college students worldwide: a knowledge mapping approach. Humanit Soc Sci Commun 11 , 1353 (2024). https://doi.org/10.1057/s41599-024-03781-0

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The Impact of Social Media on Mental Health

1. introduction.

Though social media has its benefits, its relationship with mental health is complex and multifaceted. Although academic research in the area is still scarce, there is an increasing interest in the impact of cyberbullying, scamming, and catfishing, as well as common technology addiction patterns connected with depression and anxiety. Due to increasing interest but lacking research and academic literature, we conducted a systematic review of peer-reviewed academic literature in the major academic publication databases. The number of publications has been increasing since 2013, showing the importance and attention given by academics to the subject. The results of the conducted visualization on knowledge discovery in academic databases show that most researchers focus their studies on common mental health disorders like anxiety, stress, and depression linked with diverse social media habits and cyberbullying. Some also studied related concepts like the negative impact of internet use on social isolation, low friendship quality, low self-esteem, body dissatisfaction, reduced social belonging, reduced social connectedness, increased narcissism, conceptualization of self, and reduced social capabilities. The major social media platforms, only incidentally mentioned in research questions, were Facebook, Twitter, Instagram, and Snapchat. This systematic review presents a comprehensive overview of existing academic literature on social media studies with mental health links, thus contributing to the understanding of the mental health impacts of social media by highlighting gaps in current research and important areas for future work.

2. Literature Review

Studies now show that participation in social media not only can drive emotional distress, but in some cases contribute to, or even exacerbate, symptoms of diagnosable mental illness in people. The greater concern, however, is that subthreshold or undiagnosed mental health difficulties may be worsened by continued exposure to the curated images of others' lives, which are usually surfaced on platforms. This study intends to explore, critique, and disentangle the impact of social media exposure on mental health in adolescents. We find evidence that although increasing use of these platforms is not directly translating to worsening outcomes in the way that had been initially anticipated, some subgroups of users are affected detrimentally by their exposure. Evidence of impacts in both directions is, however, inconsistent, potentially biased, and underspecified. Cross-sectional and short-term panel designs without any kind of control suggest a strong association between both very high and very low engagement and problematic health behaviors. Characteristically, most papers explore negative effects of exposure only, rather than considering the impact on health of having a social media account or indeed not having one. Bespoke data reconstructions for the present paper from a prominent state government epidemiological dataset at the school district level, combined with measurement of social media engagement at the student level, provide a singularly powerful opportunity to isolate both dimensions of exposure to various forms of digital media, as well as control for many other known patterns or predictors of mental health and substance use among adolescents.

2.1. Positive Effects of Social Media on Mental Health

The relationship between social media and mental health is controversial. Many researchers have found that young people who use social media extensively tend to have more mental health problems. At the same time, social media has been utilized as a tool to improve the mental health of individuals. In this study, we attempted to clarify these contrasting findings. To do this, we conducted a structured expert interview study and defined social media content designed for mental health improvement. Users who are good at creating and recognizing attractive mental health content can play an important role in orienting the behaviors of young people to use social media more positively. For young people, the benefits of using social media and its possible contributions to their mental health become clear when they recognize a variety of social media content that is designed for mental health. Our suggested mental health content designed for social media, positive effects, and potential contributions of social media are expected to further develop and support traditional non-pharmacological digital interventions. Our approach enables us to unlock the potential of social media as a tool for mental health improvement.

2.2. Negative Effects of Social Media on Mental Health

The negative effects of social media on mental health have also been studied in recent years. Many of the negative effects of social media on mental health are related to the fact that people feel the pressure to present themselves in the best possible light. Even though there is a clear increase in the use of social media, there is also a decrease in mental well-being. Social media bullying, solidarity, and social comparison can affect people in different ways. The fear of missing out, social media loneliness, overuse of social media, and negative consequences are also associated with an increased risk of mental health problems. The fear of missing out is a distressing feeling that other people are having fun without you, especially reinforced through social media with the posts on social events and contacts being celebrated by friends. The frequent use of social media increases mental health distress due to this fear, and the user needs other coping mechanisms to manage this feeling. When individuals make social comparisons online, they feel worse about themselves when they see themselves as below the industry standard. They feel better when they are above the standard. The upward social comparisons have negative effects that digital platforms can exert on the emotional well-being of the individual. Those comparisons to other people's highlight reels breed insecurity. The result is a negative self-perception. This involves increased depression, stress, crushing anxiety, and insecurity. The excessive use of social media is associated with low self-esteem and depression. The main reason is that social media immersion is linked with greater dissatisfaction about life satisfaction. Too much time on social media with favorable comparisons made with others would lead to dissatisfaction believed to be in the fashion industry. That dissatisfaction may then predict the symptom of body dissatisfaction leading to more pervasive body-image problems. The prior studies affirm that body dissatisfaction is linked to depression.

3. Methodology

Data Collection Sources For the purpose of data collection, a free web-based source focused on gathering data related to the overall assessment and engagement of individual brands, companies, or products, following the principles of social media listening. Additionally, it combines social media search and analysis functionalities. Although this tool is a compromise due to the absence of advanced custom search setup, it simultaneously processes a wide range of social platforms. Selection of Platforms Mood-related data collection included two social networks—Twitter and Facebook—for the entire year of 2020. Both of them belong among the top six most frequented platforms worldwide. Twitter reports more than 330 million active users per month with a significant increase in tweets mentioning “mental health” in the United Kingdom over the past year. Facebook, on the other hand, estimates more than 2.7 billion active users per month and a significant increase in sharing Odds Ratio values in terms of mental health toleration as well. To provide a diversified sample of the collected data, official keywords frequently mentioned in the UK’s mental health surveys, such as “depression,” “anxiety,” “overwhelm,” “wellbeing,” and “self-care,” were chosen.

4. Findings and Analysis

4.1 Bivariate Analysis for Independent Variables Results of this analysis are presented below, and relationships are discussed in the context of literature definitions beforehand. 4.1.1 Age and Life Satisfaction Using one-way ANOVA, results on age and life satisfaction show that there are significant differences in life satisfaction depending on the age group of respondents. The p-value is 0.037, which is less than 0.05. The mean scores indicate that life satisfaction decreases with an increase in age. 4.1.2 Level of Income or Financial Status There is a significant relationship between life satisfaction and the financial status of individuals. Poor people are not able to satisfy their needs and are thus less satisfied with their lives than those individuals with higher incomes and wealth. 4.2 Bivariate Analysis for Social Media and Mental Health Regression analysis was conducted to find if social media platforms affect mental health. Dependent variables included Life Satisfaction and the relationship between Mental Health and the use of social networks, chat, e-commerce, relationships among blog users, and social capital. 4.2.1 Use of Social Network With this regression, the relationship between life satisfaction, mental health, and social network use was found to be statistically significant. - Since the p-value was less than 0.05, there is evidence to reject the null hypothesis in favor of the alternative hypothesis. - In turn, the use of social networks in activities such as communicating with friends, reading, and exchanging information can have an effect on an individual's life satisfaction and general mental health.

5. Recommendations and Conclusion

While there are several negative impacts that social media has on mental health, there are also a number of positive aspects of social media that cannot be ignored: social media can have positive impacts on health if used in a productive way. To lower the negative impact of social media on mental health and increase its benefits, there are a number of recommendations. Included recommendations are that mental health professionals should 1) educate and raise awareness of social media's impact on mental health, 2) empower youth to have a healthy relationship with social media, 3) take an integrated approach to social media, and 4) provide information and resources to parents with struggling children. Social media can no doubt have negative impacts on mental health. However, there are also several positive aspects that social media has on mental health, which are fueling a new field of study and the development of intervention research. Since mental health professionals are at the frontlines of mental health and may be equipped with knowledge and skills in helping people with mental health problems affected by social media, they should start now to leverage the positive aspects presented, work together to understand and manage the negative aspects for better mental health, and harness the overall impact for a healthier society.

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Understanding Social Media Literacy: A Systematic Review of the Concept and Its Competences

Karina polanco-levicán.

1 Programa de Doctorado en Ciencias Sociales, Universidad de La Frontera, Temuco 4780000, Chile; [email protected]

2 Departamento de Psicología, Universidad Católica de Temuco, Temuco 4780000, Chile

Sonia Salvo-Garrido

3 Departamento de Matemática y Estadística, Universidad de La Frontera, Temuco 4780000, Chile

Associated Data

Not applicable.

Nowadays, people spend long periods on social media, ignoring the implications this carries in daily life. In this context, the concept of social media literacy, an emerging concept scarcely developed in the literature, is relevant. This study sought to analyze, descriptively, the main definitions and competences of the concept of social media literacy. The methodology included a systematic search of literature in the databases Web of Science, PubMed, and Scopus between 2010 and 2021, applying filters for English and Spanish, including only scientific articles. A total of 1093 articles were obtained. An article selection process took place, applying the inclusion and exclusion criteria, resulting in a total of 15 articles being selected. The findings indicate that the concept of social media literacy is based on media literacy to then integrate the characteristics and the implications of digital platforms. This is linked to the development of cognitive competences, where critical thinking, socio-emotional competences, and technical competences are fundamental, considering the social context. The development of socio-emotional competences stands out since social media are a frequent place of interaction between people.

1. Introduction

The transformation of society has been linked to technological changes that are an important part of people’s lives [ 1 , 2 ]. Digital technologies are inserted in aspects of social life, in families and relations with others, at work, in governance and political participation, and they generate new ways to shape a community [ 3 , 4 , 5 ]. In this sense, social media are widely used by different societies, transcending the geographical borders of territories and cultures, connecting the global to the local [ 6 , 7 ]. Staying on the Internet and social media for extended periods has resulted in media and digital literacy continuing to gain importance [ 1 ].

It is important to specify that social media differ from other types of Internet platforms in that they are characterized by their mass use, they allow content creation, and are not only consumed passively, making it possible for people who do not have formal knowledge about mass media to produce information [ 8 ]. This is even more relevant considering the cross-sectional use of social media by different age groups and that children’s exposure to cell phone screens begins at an early age [ 9 ]. Later, in adolescence they spend extensive periods on social media due to their socializing with their peers [ 10 , 11 ], whereas university students spend an average of 20 h a week on such digital platforms [ 12 ], it has been reported that 98.3% of survey respondents state they use social media [ 13 ]. The opposite would mean being outside a relevant social space [ 14 ]. In the older adult population, there is evidence that they use the technology less other age groups; however, the rates of social Internet use are increasing [ 15 ].

It should be noted that users are exposed to different phenomena on social media, such as publicity, images with a positivity bias, and aggressive and violent behaviors. In addition, the way in which social media operate must be considered as they use technology to filter content based on the users’ previous choice, favoring confirmation bias [ 16 ]. They also offer the opportunity to choose with whom one wishes to interact, enabling the formation of groups or communities with similar characteristics [ 17 , 18 , 19 ], which can foster negativity against what is different, which can be particularly relevant in phenomena such as cyberbullying, which has been linked to time spent on social media [ 20 , 21 ].

Thus, there are also messages on social media that can be potentially harmful when they are about health and personal appearance [ 22 ], considering people’s exposure to advertising and photos shared with positivity biases [ 23 , 24 ]. In this sense, exposure to photos that have been manipulated to achieve a positive appearance is associated with reducing body image and body satisfaction, with the increase in the desire of young women to get cosmetic surgery [ 25 ], depending on the time spent on the Internet [ 23 ].

On the other hand, users can be confronted with demands and difficulties such as the dissemination of false and manipulated news in the post-truth era [ 1 , 26 ], which are produced and put into circulation intentionally to obtain benefits such as more visits by users [ 27 ]. This is combined with people sharing information without a review process for this content since positive feedback from other users prevails; consequently, fake news goes viral very quickly [ 26 ]. People are needed in the role of information consumers; they must develop critical thinking, i.e., a skeptical view of the selection of the news provided through algorithms and the news sources must be tracked [ 4 , 26 ], since discerning veracity or falsity is a responsibility that transcends the individual [ 5 ].

It is important to note that the use of social media is not negative in itself as it can increase social capital, foster friendships and reduce feelings of loneliness; however, it depends on the user’s characteristics and how the different platforms are used [ 28 , 29 ]. As a result, teaching and learning competences for the use of these Internet platforms are particularly relevant since they include social and ethical aspects and technical skills [ 14 ], as well as competences that can assess information that aids in better decision-making [ 30 ].

Media literacy was defined by the Aspen Institute [ 31 ] as “the ability to sensitize, analyze and produce information for specific results” (p. 6), although this conceptualization has certainly undergone progressive transformations, moving from printed information to expression and communication that includes new symbolic forms, such as images and multimedia content. In addition, social media have enabled group collaboration and the dialogue of a large number of people who produce content [ 32 ]. It is worth noting that Hobbs [ 32 ] refers in particular to media literacy and understands it as knowledge, competences, and skills for life that make it possible to participate in today’s society by accessing, analyzing, evaluating, and creating messages in different ways and in different media, being the result of media education. For his part, Buckingham [ 33 ] emphasizes the critical component and the understanding that contents are inserted in a broad context, for example, digital capitalism. The emergence of new types of literacy is linked to the appearance of Internet and mobile communication technologies, which have resulted in the appearance of new media. Considering their impact, this is occurring with technologically based sociocultural platforms [ 34 ].

In the same vein, digital literacy refers to a broad set of competences around the use of digital media, computers, and information and communication technologies (ITC), being understood as part of other forms of literacy, such as computer, Internet, media, and informational literacy [ 35 ]. Currently, efforts are being made by the international community to guarantee digital literacy [ 36 ], because since the COVID-19 pandemic time on the Internet and social media has increased [ 37 ]. It is important to mention that digital literacy has been proposed as a strategy against social inequality, given the connection between technological exclusion and wider forms of economic and social exclusion [ 38 ], because people have fewer opportunities to develop skills due to their limited Internet connection, thereby reducing participation levels [ 39 ]. Another relevant element is that it is linked to socio-economic disadvantage with a lack of knowledge about the algorithms that these types of platforms use to recommend content [ 40 ].

Literacy in traditional and digital media is central given that we live permanently receiving messages from different sources [ 41 ]. Generally, these are focused on improving people’s competences to integrate and operate in today’s society [ 42 ]. Therefore, it is necessary to promote the development of skills such as critical thinking because even though teenagers and young adults have known the world with the Internet, they do not have better developed skills in all the areas that digital literacy addresses [ 43 ]. Nevertheless, according to Leaning [ 35 ], the difficulty arises because media literacy does not sufficiently address digital technology, considering that digital literacy does not fully develop a critical approach compared to media literacy. However, it is relevant to point out that the boundaries between the types of literacy can be blurred; in addition, other proposals progressively emerge that link different approaches such as critical digital literacy, rendering the desired distinctions complex [ 44 , 45 , 46 ].

In this sense, due to their mass use, social media have transformed the way we relate to each other, form communities, and use mass media. This has been of interest, with proposals on the issue of literacy being generated that focus particularly on these digital platforms. Therefore, Livingstone [ 47 ] indicates the need for literacy focused on social media to update the analysis of media literacy. Nevertheless, this concept has limited theoretical development and little operationalization [ 7 , 48 ]. In addition, there is evidence that authors define it differently; it has not been clearly established what the competences are that are included in this type of literacy given the authors working with this concept in their research.

In light of the above, this article focuses on social media literacy by performing a systematic literature review to better understand the concept in terms of the competences it provides that adequately guide efforts in the direction of teaching and learning processes in this area. The relevance of these processes must be borne in mind due to the mass use of such platforms and their use by people of different ages for extended periods, considering there are dangers in social media while at the same time they afford possibilities for interaction, entertainment, and other options that can be useful with an adequate understanding of how social media work and how to make use of them. Therefore, the aim of this study was to analyze, descriptively, the main definitions and competences of the concept of social media literacy.

2. Materials and Methods

A systematic search of the literature was done, considering the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 49 ], in the Web of Science, PubMed, and Scopus databases in July 2021. The question that guided the search strategy was: what are the competences that must be developed to operate on social media? The search took place using free terms and terms from Medical Subject Headings (MeSH) including social media, social media sites, digital literacy, media literacy, and social media literacy. The filters were: language (English and Spanish), number of years (from 2010 to date), and article type (article). With respect to the total articles ( n = 1039), they were first selected by relevant title, second, by relevant abstract. Then, the articles were reviewed in full ( n = 59), and the inclusion and exclusion criteria were applied, resulting in 15 articles ( Figure 1 ).

Systematic review flowchart (Adapted from Page et al., 2020 [ 49 ]).

2.1. Criteria for Eligibility

Inclusion criteria: Articles were selected that proposed a conceptual definition of social media literacy and/or that demonstrated the competences that integrate this concept. Articles were included where the participants were children, teenagers, young adults, adults, and families. Only scientific articles, theoretical and empirical, in English and Spanish between 2010 and 2021 were included.

Exclusion criteria: Articles that address social media from digital literacy without specifically considering the scope of social media literacy were not included, since they do not define the concept, nor do they refer to the competences that social media literacy encompasses. In addition, articles that address digital platforms but do not consider social media were not included. Theses, conference proceedings, and systematic reviews were not included. Articles in languages other than English or Spanish or with a publication date before 2010 were also excluded.

2.2. Procedure

Articles were selected considering the inclusion and exclusion criteria. The articles also had to provide information that responded to the research question; therefore, those articles that did not fit as previously indicated were eliminated. Where questions or disagreements arose about the selected articles, they were resolved through the joint review by the two authors to determine their relevance and to make a decision about their inclusion.

In terms of biases of this study, the language bias was countered by including articles in Spanish and English. In terms of coverage bias, the different databases (Web of Science, Scopus, and PubMed) were reviewed.

2.3. Analysis Strategy

With respect to the selection final, the articles were read and reviewed completely, observing if the records provided a conceptual definition of social media literacy or if they reported on the skills that this type of literacy includes. The other criteria of inclusion and exclusion were also considered. The standard quality assessment criteria for evaluating primary research papers were also applied [ 50 ].

Later, a table was constructed to present the studies, considering first the authors, type of study, objective, and information on the sample. Then, the main results were transformed in relation to the research question to report on the studies selected and to organize the findings of this study.

In relation to the biases present in articles, generally the records describe full data in their results; moreover, the results were reported according to the analyses used, considering that this is of interest to this review.

Fifteen articles were obtained for analysis from the following countries: Australia, Belgium, the Czech Republic, Germany, Indonesia, Singapore, Spain, the United Kingdom, and the United States, it being observed that interest in the concept of social media literacy is concentrated mainly in European countries that develop and contribute theoretical and empirical evidence relating to this concept ( Table A1 in Appendix A ).

3.1. Social Media Literacy: Definition

The conceptualization of social media literacy is based on media literacy [ 51 , 52 , 53 , 54 , 55 , 56 , 57 ]. However, it is emphasized that social media are oriented to the interpersonal communication that arises from the human need to establish interactions with others [ 48 , 52 , 53 ]. Thus, according to Vanwynsbergue [ 56 ], the focus would be on favoring the efficiency and efficacy of Internet communication, benefitting social relations ( Table A1 in Appendix A ).

On the other hand, the understanding of the particular characteristics of such platforms is worth noting, in that it is relevant how the information is presented on social media, considering the objectives after posts by both people and advertising, in addition to positivity bias [ 51 , 53 , 54 ]. Consequently, social media literacy is oriented towards the prevention of risks such as mental and physical health problems [ 51 , 53 ], as well as other types of consequences that can arise from interactions between people, for example cyberbullying, information spreading, and other difficulties [ 52 , 53 , 55 ].

3.2. Social Media Literacy: Competences

With respect to the different competences that encompass social media literacy according to the different studies, there is evidence that cognitive competences appear cross-sectionally in most of the studies searched. These include understanding, analysis, evaluation, synthesis, and the interpretation of the information, added to the assessment of the motive, purpose, realism, and credibility of the publication. Critical thinking is considered fundamental due to the large volume of information to which social media users are exposed [ 51 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ]. In addition, according to Schreurs and Vandenbosch [ 54 ], cognitive competences include a knowledge of traditional media literacy and the dynamics of interpersonal communication on social media ( Table A1 in Appendix A ).

Similarly, user-generated information requires that they have knowledge of the implications of sharing personal data and the generation of information considering the digital fingerprint, since this information is used by the social media platforms and shared with other companies, so the user must evaluate what content to share [ 62 ]. Likewise, Tandoc et al. [ 63 ] report on the need to raise awareness about the content recommendation algorithms that transform the social media experience.

The technical or practical competences include the ability to create, review, organize and share contents [ 57 , 58 ], access, find information and use functions such as privacy settings [ 62 ], create social media accounts and publish photos and images, and make videos and memes [ 60 , 63 ]. These competences fulfill an important role so people of different ages can perform adequately on these digital platforms [ 51 , 55 , 56 , 57 , 58 , 59 , 60 ].

On the other hand, the socio-emotional competences are integrated by several authors into the conceptualization of social media literacy because such digital platforms are oriented to the interaction between different people who share content online; therefore, management strategies for interpersonal communications are relevant [ 48 , 51 , 54 , 55 , 56 , 63 ]. Festl [ 48 ] proposes that the development of social competences is central to social media literacy including participation and moral, communicative, and education competences, consistent with other studies that lend relevance to motivation, attitude, and behavior that people on social media exhibit [ 55 , 56 ]. In addition, Schreurs and Vandenbosch [ 54 ] note that effective competences are reflected in the use of adaptive strategies when users are exposed to difficulties on social media, as indicated in Appendix A ( Table A1 ).

The proposals of authors that consider the relevance of the context in which social interactions occur as well as the language used on social media are worthy of note. Specifically, the differences between the different digital platforms must be taken into account since they have particular ways of operating [ 55 ]. Moreover, the sociocultural pragmatics in the different social media must be borne in mind, i.e., changes in the users’ language, relations, and behavior depending on the different social and cultural contexts that take place on the Internet [ 57 ]. This would make it possible to assess the context that could help discern veracity of the information [ 60 ], considering the increase in fake news [ 63 ].

4. Discussion

The objective of this study was to analyze descriptively the main definitions and competences of the concept of social media literacy. The results yielded 15 studies ( Table A1 in Appendix A ) that address social media literacy by either conceptualizing it, or by referring to the competences of which it consists. It should be noted that there are studies that, despite using the concept in their articles, do not develop it, or they use it to talk about another type of literacy without making a suitable distinction on the issue [ 22 , 64 , 65 ].

In relation to the findings of this study, the construction of the concept of social media literacy is based on the knowledge gained through media literacy, to then integrate elements focused on catching the particularities, characteristics, and implications of social media. In this context, it is fundamental to consider the social interactions produced on social media, the possibility of users creating content, the large amount of information that circulates on social media that includes user content and publicity from businesses, as well as the content filtering and recommendation technology. In the same vein, it is suggested that the concept of social media literacy could respond to the requirements of today’s society due to the mass and recurring use of these types of virtual platforms worldwide [ 47 , 48 , 51 , 52 , 53 , 54 , 55 , 56 ].

Consequently, social media literacy is an update of media literacy [ 47 ], being oriented to favoring people being able to perform adequately on social media considering the various difficulties that can arise. Without a doubt, the phenomena that occur on social media are not all negative, rather these digital platforms have benefits that could be taken advantage of better if users have greater knowledge and competences [ 28 ]. Thus, access to the benefits or opportunities that social media afford, such as the possibility of sharing with friends and relatives, should be promoted, but with strategies to protect against damaging trends or risky behaviors [ 54 ].

Generally, the analyzed studies converge in the relevance of cognitive competences in social media literacy. It is worth noting the development of critical thinking because most studies mention it being necessary to obtain a suitable understanding and assessment of the content, being aware of the reliability and credibility of the information [ 55 , 56 , 60 ], reducing the persuasive influence of mass media through the evaluation of the intention and realism of the content [ 53 , 61 ]. This is not an easy task due to the large volume of information and the anonymity of those who produce the content on social media [ 57 ]. In this sense, the knowledge about the algorithms with which social media work acquires relevance, presenting information to the user according to their fingerprint [ 40 ].

As Livingstone [ 52 ] points out, social media literacy is at the intersection between social and mass media, so that the relevance of socio-emotional competences stands out. The social interactions that take place between users in real time or delay time are one of the characteristics that distinguishes social media from other types of digital platforms or mass media; therefore, different authors have focused on the socio-emotional competences to conceptualize and operationalize the construct [ 48 , 51 , 52 , 53 , 54 ]. In this way, such competences can be considered a protective factor against cybervictimization [ 66 ], and a greater prosocial behavior in Internet activities is implied [ 67 ], since there are adaptive strategies against negative experiences [ 54 ].

With respect to the technical or practical competences, there is evidence that among these are the ability to access, create, review, and share content on social media, adding other functions such as those linked to privacy settings. These competences are considered in a general way; however, social media platforms are different from each other, which is why it is relevant to consider those specific skills that could help people to perform adequately on the different social media. Coincidently, Manca et al. [ 7 ] refers to a higher skill level that can be cross-sectional on the different social media and skills specific to each digital platform.

Likewise, studies have shown the relevance of the context in which the content is generated in order to assess its construction [ 55 , 57 , 60 ]. Then, the specific platform can be considered, the context in which differences in the language used and the forms of interaction between users are reflected. On the other hand, it is important to place social media within a broader social and economic context such as digital capitalism [ 33 ], being aware of the objectives of the social media companies such as generating profits [ 68 ], transforming the private experience into merchandise [ 69 ].

Another finding of this study is the different areas in which studies are being conducted that involve this concept. On the one hand, evidence shows that different authors work with this concept applied to the area of physical and mental health related to body perception [ 51 , 53 , 61 , 70 ], developing interventions to reduce eating disorders and the negative impact of exposure to social media because they show idealized appearances, such that social media literacy is considered a protective factor [ 24 , 61 ]. Meanwhile, another group of authors focuses on research with children and adolescents due to the continuous use of social media as a result of their need to establish relations with their peers and how their families mediate the use of digital platforms [ 48 , 52 , 54 , 58 ]. Consequently, the development of competences by teenagers is fundamental for them to operate suitably on social media, considering that parents show deficiencies in technical competences and knowledge of social media because they use them less or they use digital platforms passively [ 54 , 58 ].

Finally, the relevance of the analysis and the assessment of news content on social media to determine its veracity stands out in the current context [ 5 , 26 , 60 , 63 ]. In this sense, the contribution of social media literacy is significant since it considers aspects of such platforms, because when sharing information, it prioritizes the expectation of positive feedback from other users, or that the content supports one’s personal beliefs and values.

5. Conclusions

This systematic review collaborated in the understanding of the construct of social media literacy in its definition and the skills that integrate it, being considered an area of emerging research and that its development is very necessary due to people staying on social media specifically for extended periods. Social media literacy is focused on the development of different abilities that range from the technical to the socio-emotional. In this sense, social media, by making possible and favoring social interactions, bring with them requirements for people to perform adequately on digital platforms, understanding that there is no separation between the digital plane and the physical plane; therefore, a mutual influence is produced that could affect people’s experience by being exposed to the dangers on social media that worsen without the skills to deal with such situations.

On the other hand, the social, economic, cultural, and political context is integrated into the analysis conducted on social media given that such platforms have product advertising, political announcements, and other situations to which social media users are exposed. At the same time, the social media differ from each other, so it is relevant to visualize the characteristics of each of them and their differences, noting they each have their own culture that is reflected in the language, behavior, and interactions generated.

In terms of the limitations of this study, it should be noted that there may be articles that were not detected in the systematic search, or that were not selected for the analysis considering the inclusion and exclusion criteria of this study because the authors used concepts linked to media and digital literacy to refer to the concept of social media literacy. Other databases could be added to verify whether there are new articles and integrate them into the results, contributing to different research questions. Similarly, other types of articles such as systematic reviews or conference proceedings could be added since they were excluded here. With respect to the future lines of investigation, studies must be generated considering the construct of social media literacy and its relation to other constructs such as cyberbullying and cyberaggression as the dangers of social media are considered, making it possible to observe which competences that make up social media literacy are those that would mainly protect against these dangers. In addition, it would be interesting to identify the relations with constructs that reflect if social media literacy facilitate the opportunities that such platforms offer. Finally, other studies could broaden the inclusion criteria by incorporating articles that address social media literacy, although the authors have used other broader concepts or approaches in their research. This way, future studies could analyze and evaluate which of the different literacies that focus on social media obtain the best results.

Concept and competences of Social Media Literacy.

Funding Statement

K.P.-L. received financial support by the National Agency for Research and Development (ANID)/Scholarship Program/DOCTORADO BECAS CHILE/2020-21200712.

Author Contributions

Conceptualization, K.P.-L. and S.S.-G.; methodology, K.P.-L. and S.S.-G.; formal analysis, K.P.-L. and S.S.-G.; investigation, K.P.-L. and S.S.-G.; data curation, K.P.-L. and S.S.-G.; writing—original draft preparation, K.P.-L. and S.S.-G.; writing—review and editing, K.P.-L. and S.S.-G.; supervision, K.P.-L. and S.S.-G.; All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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Why Marketers Are Spending Less on Social Media

by Christine Moorman and Koen Pauwels

Summary .   

A bi-annual poll of U.S. marketing leaders found that social media investments have declined to their lowest level in seven years. An analysis of poll data suggests that lack of strategy fit, weak returns, and new competition from retail media may help explain this dip. Researchers leverage their findings to offer suggestions to marketers on how to overcome past strategy misalignment in order to continue to benefit from social media’s immediacy and pervasiveness, including through the use of Gen AI.

In June 2020, social media spending surged to 23% of marketing budgets when the pandemic forced consumers to stay home and marketers pivoted to digital channels for outreach.   A new, heightened focus on social media accelerated the digitization of marketing so that by 2022, fully 57% of spending was dedicated to digital marketing. The recent adoption of new marketing technology (Martech) to automate processes and the use of AI to generate content have driven digitization further into business models.

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