research article on tiktok

MINI REVIEW article

On the psychology of tiktok use: a first glimpse from empirical findings.

• 1 Department of Molecular Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
• 2 The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
• 3 Faculty of Psychology, Tianjin Normal University, Academy of Psychology and Behavior, Tianjin, China
• 4 Department of Psychology, University of Toledo, Toledo, OH, United States
• 5 Department of Psychiatry, University of Toledo, Toledo, OH, United States

TikTok (in Chinese: DouYin; formerly known as musical.ly) currently represents one of the most successful Chinese social media applications in the world. Since its founding in September 2016, TikTok has seen widespread distribution, in particular, attracting young users to engage in viewing, creating, and commenting on “LipSync-Videos” on the app. Despite its success in terms of user numbers, psychological studies aiming at an understanding of TikTok use are scarce. This narrative review provides a comprehensive overview on the small empirical literature available thus far. In particular, insights from uses and gratification theory in the realm of TikTok are highlighted, and we also discuss aspects of the TikTok platform design. Given the many unexplored research questions related to TikTok use, it is high time to strengthen research efforts to better understand TikTok use and whether certain aspects of its use result in detrimental behavioral effects. In light of user characteristics of the TikTok platform, this research is highly relevant because TikTok users are often adolescents and therefore from a group of potentially vulnerable individuals.

Musical.ly was founded in September 2016 by Zhang Yiming. Beijing Bytedance Technology acquired the application musical.ly in November 2017 and renamed the app to TikTok. In a short time period, this application became the most successful app from Chinese origin in terms of global distribution ( 1 ). As of November 2020, 800 million monthly users have been reported 1 , and 738 million first-time installs in 2019 have been estimated 2 . TikTok use is allowed for those 13 years or older, but direct messaging between users is allowed only for those 16 or older (in order to protect young users from grooming) 3 . In China, the main users of TikTok are under 35 years old (81.68% (2)). Meanwhile, to protect children and adolescents from unsuitable content (such as smoking, drinking, or rude language), TikTok's engineers also developed a version of the app, which filters inappropriate content for young users ( 2 ). Of note, at the moment of writing, the app operates as TikTok on the global market and as DouYin on the Chinese market ( 3 ). Similarities and differences of the twin apps are further described with a content analysis by Sun et al. ( 4 ).

The TikTok application available for Android and Apple smartphones enables creation of short videos where users can perform playback-videos to diverse pop-songs, to name one very prominent feature of the platform. These so-called “LipSync-Videos” can be shared with other users, downloaded for non-commercial purposes, commented upon and of course attached with a “Like.” Not only are playback-videos uploaded on TikTok but also users view a large amount of video content. Users can also call out for “challenges,” where they define which performance should be created by many users. As a consequence, TikTok users imitate the content or interact with the original video.

As the large user numbers in a very short time-window demonstrate, TikTok not only represents a global phenomenon but also has been criticized with respect to data protection issues/privacy ( 5 , 6 ), spreading hate ( 7 ) and might serve as a platform engendering cyberbullying ( 8 , 9 ). Given the many young users of this platform (e.g., 81.68% of China users of Tiktok are under 35 years old—see above, and 32.5% of the US users are 19 years old and younger) 4 , it is of particular relevance to better understand the motivation to use TikTok, alongside related topics. Such an understanding might also be relevant because recent research suggests that TikTok can be a potent channel to inform young persons on health-relevant information ( 10 – 12 ), on official information release from the government ( 13 ), political discussions ( 14 ), tourism content ( 15 ), live online sales ( 16 ), and even educational content ( 17 ). There even have been video-posts analyzed in a scientific paper related to radiology ( 18 ). Clearly, young TikTok users are also confronted with harmful health content, including smoking of e-cigarettes ( 19 ). Moreover, the health information learned from TikTok videos often does not meet necessary standards—as is discussed in a paper on acne ( 20 ). Finally, there arises the problem that while creating content, children's/adolescent's private home bedrooms from which they create TikTok videos become visible to the world, posing privacy intrusions ( 21 ). The many obviously negative aspects of TikTok use are in itself important further research leads. From a psychological perspective, we take a different path with the present review and try to better understand why people use TikTok, who uses the platform, and also how people use TikTok.

Why do People Use TikTok?

This question can be answered from different perspectives. One perspective providing an initial answer and—likely being true for most social media services—has been put forward by Montag and Hegelich ( 22 ). Social media companies have created services being highly immersive, aiming to capture the attention of users as long as possible ( 23 ). As a result of a prolonged user stay, social media companies obtain deep insights into psychological features of their users ( 24 ), which can be used for microtargeting purposes ( 25 ). Such immersive platform design also likely drives users with certain characteristics into problematic social media use ( 26 ) or problematic TikTok use (addictive-like behavior), but this aspect relating to TikTok use is understudied. Nevertheless, reinforcement of TikTok usage is also very likely reached by design-elements such as “Likes” ( 27 ), personalized and endless content available ( 23 ). TikTok's “For You”-Page (the landing page) learns quickly via artificial intelligence what users like, which likely results in longer TikTok use than a user intended, which may cause smartphone TikTok-related addictive behavior ( 2 ). This said, these ideas put forward still need to be confirmed by empirical studies dealing exclusively with TikTok. In this realm, an interesting research piece recently investigated less studied variables such as first-person camera views, but also humor on key variables such as immersion and entertainment on the TikTok platform ( 28 ), again all of relevance to prolong user stay.

The other perspective one could choose to address why people use TikTok stems from uses and gratification theory ( 29 , 30 ). The simple idea of this highly influential theory is that use of certain media can result in gratification of a person's needs ( 30 ), and only if relevant needs of a person are gratified by particular media, users will continue media use—here digital platform or social media use.

A recent paper by Bucknell Bossen and Kottasz ( 31 ) provided insight that, in particular, gratification of entertainment/affective needs was the most relevant driver to understand a range of behaviors on TikTok, including passive consumption of content, but also creating content and interacting with others. In particular, the authors summarized that TikTok participation was motivated by needs to expand one's social network, seek fame, and express oneself creatively. Recent work by Omar and Dequan ( 32 ) also applied uses and gratification theory to better understand TikTok use. In their work, especially the need for escapism predicted TikTok content consumption, whereas self-expression was linked to both participating and producing behavior. A study by Shao and Lee ( 33 ) not only applied uses and gratification theory to understand TikTok use but also shed light on TikTok use satisfaction and the intention to further use TikTok. In line with findings from the already mentioned works, entertainment/information alongside communication and self-expression were discussed as relevant use motives (needs to be satisfied by TikTok use). Satisfaction with TikTok was investigated as a mediator between different motives to use TikTok and to continue TikTok use. We also mention recent work being unable to link TikTok use to well-being, whether in a positive or negative way ( 34 ). Finally, Wang et al. ( 35 ) underlined the overall relevance of uses and gratification theory to understand TikTok use and presented need variables in cognitive and affective domains as relevant to study, but also personal/social integration and relief of pressure. In this context, we also mention the view of Shao ( 2 ) who put forward that, in particular, young people use TikTok for positioning oneself in their peer group and to understand where he/she stands in the peer group. Thus, TikTok is also relevant for identity formation of young persons and obtaining feedback to oneself.

Further theories need to be mentioned, which can explain why people are using the TikTok platform: Social Impact Theory and Self-Determination Theory. To our knowledge, these theories have not been sufficiently addressed empirically so far with respect to TikTok use, but are well known to be of relevance to understand social media use in general and are therefore mentioned.

Clearly, an important driver of social media use can be power, hence, reaching out to many and influencing other persons ( 36 ). Here, the classic Social Impact Theory (SIT) by Latané ( 37 ) tries to understand how to best measure the impact of people on a single individual/individuals. This theory—originating in the pre-social-media-age—gained a lot of visibility with the rise of social media services because, in particular, in the age of filter bubbles, fake news, and misinformation campaigns ( 38 , 39 ), it is interesting to understand how individual users on social media are socially influenced by others, for instance, in the area of their (political) attitudes. The SIT postulates three highly relevant factors called strength, immediacy, and number (of sources) to predict such a social impact. Ultimately, applying this theory to better understand TikTok use also needs to take into account that users differ in terms of their active and passive use.

The Self-Determination Theory (SDT) has been proposed by Ryan and Deci ( 40 ) and belongs to the most influential motivation theories of human behavior. Hence, it clearly can also be used to explain why people are motivated to use a social media service ( 41 , 42 ). According to SDT, motivated behavior (here using TikTok) should be high, when such a platform enables users to feel competence, autonomy, and being connected with others. Design of the platform can help to trigger related psychological states (e.g., push notifications can trigger fear of missing out, hence, not being connected to significant others) ( 43 ); but clearly also, individual differences play a relevant role, and this should be discussed as the next important area in this work. As with the SIT, applying SDT to better understand TikTok use will also need to take into account different kinds of TikTok use. A sense of self-determination might rise to different levels, when users are actively or passively using TikTok—and this also represents an interesting research question.

Who Uses TikTok and Who Does Not?

The aforementioned statistics show that TikTok users are often young. Bucknell Bossen and Kottasz ( 31 ) illustrated that, in particular, young users are also those who seem to be particularly active on the platform, and thus share much information. Given that, in particular, young users often do not foresee consequences of self-disclosure, it is of high importance to better protect this vulnerable group from detrimental aspects of social media use. Beyond age, statistics suggest that more females than males use the platform 5 , something also observed with other platforms ( 44 – 46 ). First, insights from personality psychology provided further information on associations between characteristics of TikTok users and how they use it (see also the next How Do People Use TikTok? section): The widely applied Big Five Personality traits called openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism (acronym OCEAN) were all robustly linked to producing, participating, and consuming behavior on TikTok, with the exception of agreeableness only being linked to consuming behavior ( 32 ). Using a hierarchical regression model inserting both personality variables and motives from uses and gratification theory, it became apparent that the latter variables seemed to outweigh the personality variables in their importance to predict TikTok usage. Lu et al. ( 47 ) used data from China to investigate individual differences in DouYin (again the Chinese version of TikTok) use. Among others, they observed that people refraining from using DouYin did so out of fear of getting “addicted” to the application [see also ( 48 )]. This needs to be further systematically explored with the Big Five model of personality (or HEXACO, as the personality models dominating modern personality psychology at the moment). Without doubt, it will be also highly important to better understand how the variables of socio-demographics and personality interact on TikTok use, also in the realm of active/passive use of the platform. Active use would describe a high engagement toward the platform including commenting and uploading videos. Passive usage would reflect in browsing and simply consuming videos. The need to distinguish between active and passive use of social media has been also recently empirically supported by Peterka-Bonetta et al. ( 49 ).

How do People Use TikTok?

In the Why Do People Use TikTok? section, we already mentioned that users can passively view content, but also create content or interact with others. Studies comprehensively showing how many and which types of people use TikTok with respect to these behavioral categories are lacking (but TikTok likely has at least some of these insights). A recent review by Kross et al. ( 50 ) on “social media (use) and well-being” summarized that several psychological processes such as upward social comparison (perhaps also happening in so-called “challenges” on TikTok) or fear of missing out ( 43 ) are related to negative affect and might have detrimental effects on the usage experience and/or TikTok users' lives in general. Overall, the psychological impact of the TikTok platform might also be very likely, in particular, when adolescents often imitate their idols in “LipSync-Videos” ( 51 ). The kind of influence of such behavior on the development of one's own identity and self-esteem (self-confidence) ( 52 ) will be a matter of important psychological discussion, but it is too early to speculate further on potential psychological effects here, both in the positive or negative direction ( 53 ). Moreover, whether such effects will be of positive or negative nature, we mention the importance to not overpathologize everyday life behavior ( 54 ).

In sum, much of what we know with respect to platforms such as Instagram, Facebook, WhatsApp, or even WeChat ( 56 ) needs to still be investigated in the context of TikTok, to understand if psychological observations made for other social media channels can be transferred “one-on-one” to TikTok. For instance, illustrating differences between social media platforms, Bhandari and Bimo ( 57 ) suggested in their analysis of TikTok that in contrast to other platforms, “the crux of interaction is not between users and their social network, but between a user and what we call an ‘algorithmized’ version of self.” Opening TikTok immediately results in being captured by a personalized stream of videos. Therefore, we believe it to be unlikely that all insights from social media research can be easily transferred to TikTok because it is well-known that each social media platform has a unique design also attracting different user groups ( 45 ), and they elicit different immersive or “addictive” potential ( 58 ). Please note that we use the term “addictive” only in quotation marks, given the ongoing debate on the actual nature of excessive social media use ( 59 , 60 ). This said, we explicitly mention that the study of problematic social media use represents a very important topic ( 61 ), although at the moment, this condition—of relevance for the mental health sciences—is not officially recognized by the World Health Organization. Despite the ongoing controversy, nevertheless, it has been recently pointed out that social media companies are responsible for the well-being of users, too ( 55 ).

Conclusions and Outlook

Although user numbers are high and TikTok represents a highly successful social media platform around the globe, we know surprisingly less about psychological mechanisms related to TikTok use. Most research has been carried out so far yielding insights into user motives applying uses and gratification theory. Although this theory is of high importance to understand TikTok use, it is still rather broad and general. In particular, when studying a platform such as TikTok—receiving attention at the moment from a lot of young users—more specific needs or facets of the broad dimensions of uses and gratification theory (such as social usage) being more strongly related to the needs of adolescents might need more focus. One such focus could be a stronger emphasis on the study of self-esteem ( 62 ) in the context of TikTok use. Work beyond this area, e.g., investigating potential detrimental aspects, are scarce, but will be important. In particular, we deem this to be true, as TikTok attracts very young users, being more vulnerable to detrimental aspects of social media use ( 63 ). We believe that it is also high time for researchers to put research energy in the study of TikTok and to do so in a comprehensive manner. Among others, it needs also to be studied how active and passive use impact on the well-being of the users. This means that the here-discussed how-, why- , and who- questions need to be studied together in one framework, and this needs to be done against the data business model and its immersive platform design. The key ideas of this review to understand TikTok use and related aspects such as well-being of the users are presented in Figure 1 .

Figure 1 . In order to understand the relationship between a social media service such as TikTok and human psychological processes and behavior, one needs to answer the who-, why-, and how-questions, also against the background of the social media platform design. Please note that the platform design itself is driven by the data business model. Social media usage and its association with psychological/behavioral variables such as well-being, online-time, and so on can be best understood by investigating these variables in one model, at best also investigating potential interactions of variables. These ideas have also been described in parts in Montag and Hegelich ( 22 ), Kross et al. ( 50 ), and Montag et al. ( 55 ). The figure does not exclusively mention TikTok because we are convinced that the presented details are true for all research agendas aiming at a better understanding of the relationship between social media use and well-being.

Author Contributions

CM wrote the first draft of this review article. HY screened the Chinese literature and added relevant work from a Chinese perspective to the review. Finally, JDE critically worked over the complete draft. All authors agreed upon the final version of the article.

Conflict of Interest

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

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Keywords: TikTok, DouYin, musical.ly, personality, uses and gratification, social media, social media addiction, problematic social media use

Citation: Montag C, Yang H and Elhai JD (2021) On the Psychology of TikTok Use: A First Glimpse From Empirical Findings. Front. Public Health 9:641673. doi: 10.3389/fpubh.2021.641673

Received: 14 December 2020; Accepted: 18 January 2021; Published: 16 March 2021.

Reviewed by:

Copyright © 2021 Montag, Yang and Elhai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Christian Montag, christian.montag@uni-ulm.de

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

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TikTok and teen mental health: an analysis of user-generated content and engagement

Affiliations.

• 1 Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, United States.
• 2 Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States.
• 3 Department of Psychology, University of Washington, Seattle, WA, United States.
• 4 Department of Anesthesiology & Pain Medicine, University of Washington School of Medicine, Seattle, WA, United States.
• PMID: 38950415
• DOI: 10.1093/jpepsy/jsae039

Background: TikTok is a social media mobile application that is widely used by adolescents, and has the potential to serve as a revolutionary platform for public and mental health discourse, education, and intervention.

Objective: Our study aimed to describe the content and engagement metrics of the hashtag #teenmentalhealth on TikTok.

Methods: In this study, we: (a) conducted a directed content analysis of the Top 100 TikTok videos tagged with #teenmentalhealth, and (b) collected data on video engagements (views, likes, saves, and shares) and computed view-based engagement rates.

Results: The videos collectively garnered 144,320,591 views; 28,289,655 likes; 219,780 comments; 1,971,492 saves; and 478,696 shares. Most of the generated content were from teens and therapists. Engagement metrics revealed strong user engagement rates across user types. The most prevalent content categories represented across videos were personal experience, coping techniques or treatment, humor, interpersonal relationships, and health campaign. The content categories with the highest engagement rates were relatable media representation, health campaign, social isolation, and humor. Only a single video incorporated evidence-based treatment content.

Conclusion: TikTok facilitates communication and information dissemination on teen mental health. Future research should focus on improving the quality and credibility of digital content while maintaining engagement through creativity, self-expression, and relatability. Use of popular social media platforms and community-engaged research to disseminate evidence-based content may help bridge the translational research gap.

Keywords: adolescents; dissemination & implementation science; eHealth/mHealth; psychosocial functioning.

© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: [email protected].

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Foundations and knowledge clusters in TikTok (Douyin) research: evidence from bibliometric and topic modelling analyses

• Open access
• Published: 20 September 2023
• Volume 83 , pages 32213–32243, ( 2024 )

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• Abderahman Rejeb 1 ,
• Karim Rejeb 2 ,
• Andrea Appolloni 3 &
• Horst Treiblmaier 4  

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The goal of this study is to comprehensively analyze the dynamics and structure of TikTok research since its initial development. The scholarly composition of articles dealing with TikTok was dissected via a bibliometric study based on a corpus of 542 journal articles from the Scopus database. The results show that TikTok research has flourished in recent years and also demonstrate that the authors’ collaboration networks are disjointed, indicating a lack of cooperation among TikTok researchers. Furthermore, the analysis reveals that research collaboration among academic institutions reflects the North-South divide, also highlighting a limited research collaboration between institutions in developed and developing countries. Based on the keyword co-occurrence network and topic modeling, TikTok research revolves mainly around five thematic areas, including public health, health communication and education, platform governance, body image, and its impact on children and students. Based on these findings, numerous suggestions for further research are offered. As far as the authors are aware, this is the first application of bibliometrics and topic modeling to assess the growth of TikTok research and reveal the intellectual base of this knowledge domain.

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1 Introduction

The big improvements in internet technology have boosted the widespread use of social media in numerous facets of everyday life [ 3 , 6 , 18 , 96 , 114 ]. By 2025, it is predicted that 4.5 billion individuals will be using social media platforms [ 111 ]. Making friends, communicating, delivering services, advertising, buying and selling products, seeking news, and participating in politics are just a few everyday routines that social media have influenced [ 46 , 64 , 87 ]. Conceptually, social media refers to a set of web-based tools that facilitate users’ interactions, content creation, and personal communications [ 17 , 138 ]. Beyond its personal uses, social media has also significantly impacted the corporate world. Organizations can use social media to connect with customers, promote their products and services, and collect insights into their audience [ 46 ]. It has also opened up new opportunities for advertising and marketing, enabling companies to target specific demographics and reach a larger audience [ 84 ].

As one of the most famous apps on social media, TikTok has become an important platform for content creators, brands, and companies to create content and reach an audience [ 118 ]. TikTok represents a video-sharing app where users can watch and upload clips that are 15 seconds to 60 seconds in length and edit them with special effects, lip-sync templates, and soundtracks. The unique selling point of TikTok is that each user’s feed is automatically curated based on their preferences and past interactions with the app [ 85 ]. Data from the United States shows that 32.5% of users are aged between 10 to 19, making TikTok popular with the notoriously difficult-to-reach age groups [ 45 ]. The bulk of its users throughout the world is likely to be preteens and young adults. TikTok has been conceived of as a one-of-a-kind video social media platform with unrivalled user adoption and own distinctive technological structures, making it a unique online app in which memetic features and imitation elements further enhance user interactivity and engagement [ 22 , 154 ].

Recently, scholars from several fields have numerous approaches to study the general applications of social media platforms, including TikTok [ 5 , 99 , 134 ]. As a multi-user and social-technological outlet, TikTok has been the topic of various academic discussions about its marketing [ 13 , 61 , 124 ], management, and business applications [ 90 , 147 ], as well as its use in other sectors, including education [ 48 , 108 ], healthcare [ 86 , 121 , 122 ], and tourism [ 81 , 82 , 137 , 150 ]. For example, Escamilla-Fajardo et al. [ 48 ] propose a new approach to teaching that uses TikTok and find that using this social media app in the classroom can boost student enthusiasm, make lessons more interesting, and stimulate the growth of skills such as inquisitiveness and creativity. Rand and Brushett [ 110 ] note that TikTok videos are a pleasant and casual method for students to stay up-to-date on all course-related information, enabling to close the gap between professors and students. Similarly, Khan [ 75 ] analyzes how TikTok has changed archaeology in terms of public outreach, museum exhibits, and classroom instruction. This online platform has the potential to serve as a useful tool for the development of educational environments, mainly via the facilitation of dialogue in the form of comments and user-generated responses. In the healthcare sector, Eghtesadi and Florea [ 47 ] discuss the potential of social media platforms like Reddit, Facebook, and TikTok to diffuse health-related information among the general public and medical professionals. Zheng et al. [ 149 ] evaluate the credibility of acne-related health information available on TikTok by assessing the top 100 videos matching inclusion criteria for content quality. The authors recommend that dermatologists be aware that teens are searching for acne-related content on TikTok and make acne education a top priority in this patient group. Song et al. [ 120 ] use a sample of 372 valid responses from TikTok users in China to examine the relationship between user experience and affordances and to investigate the variables that influence users’ desire to keep utilizing brief video applications to learn about health-related topics. Li et al. [ 82 ] explore the correlation between the format, kind, and content of the COVID-19 TikTok videos and quantitative metrics of user engagement such as view counts, comments, likes, and shares. In the marketing context, Yang and Ha [ 144 ] investigate the factors that drive young Chinese consumers to use TikTok and how those factors can be connected to the persuasion power of influence videos on purchases. A poll of 382 Chinese college students online throughout the country shows that people use TikTok primarily because of entertainment. By drawing on the message interpretation process framework, Deng et al. [ 41 ] seek to comprehend how TikTok users react to influencer-endorsed wine short videos and uncover segmentation variations based on gender and the generations represented (Gen Z and Gen Y). The findings indicate that product-related posts get the highest engagement on TikTok, followed by those relating to influencers, emotions, alcohol-drinking intent, behaviors, and skepticism. Finally, Dias and Duarte [ 42 ] investigate the relationship between TikTok influencers, brands, and followers, with an eye on the Portuguese market. The study’s results suggest that TikTok influencers aim to help companies by increasing their exposure and credibility, which drives more sales while acting as positive parasocial role models for their fan bases.

While the prior studies certainly provide academics with a wealth of information, there has yet to be a comprehensive bibliometric analysis of TikTok research. This comes as a surprise as a number of researchers have lately employed bibliometric techniques to investigate many academic disciplines [ 1 , 44 , 111 ]. Unlike the traditional and systematic literature reviews that necessitate substantial human coding work, bibliometric techniques enable researchers to overcome the constraints of manual approaches, such as the small sample of reviewed publications, the high potential for mistakes, and the time-consuming nature of the analysis. To this end, we apply a bibliometric and topic modeling analysis to draw attention to the interconnectedness of TikTok-related publications and examine the TikTok knowledge domain as a whole. By conducting this investigation, we have contributed at least three major additions to the current TikTok literature. First, this is the first time to examine TikTok research since its inception. As a result, exploring the structure and dynamics of scholarly articles dealing with TikTok enriches the extensive body of knowledge on the applications of TikTok. Second, we broaden the research stream of bibliometrics by analyzing scholarly TikTok-related works. Several scholars have argued that bibliometric and topic modeling techniques could be leveraged to explore the status and trends of scientific disciplines and uncover the hidden thematic structure in a larger body of literature [ 28 ]. Third, by limiting our research to scholarly works on TikTok, we contribute to this area’s growing body of knowledge. To be more specific, we seek to address the following research questions:

How has TikTok research progressed since its initial development?

What are the research status and the hotspots of academic works related to TikTok?

Which TikTok authors are the most prominent?

What are the primary features of collaboration between scholars and academic organizations on TikTok-related scholarly articles?

This study is structured as follows. The next section explains the four-step approach applied to the bibliometric analysis. Section 3 discusses the results. Section 4 presents numerous suggestions for future research based on the results of the bibliometric analysis. The last section dissects the study results, implications, and limitations.

2 Methodology

Following the four-stage method proposed by Fosso Wamba and Mishra [ 51 ], we conducted our bibliometric analysis:

Select the database and the search keywords

Carry out a preliminary analysis of data

Perform the analysis of bibliometric networks

Conduct thematic and conceptual structure analyses

Bibliometrix, R software, ggplot2, rentrez, and wordcloud were some of the tools used in the study. The bibliometric networks were also generated and shown with the help of VOSviewer [ 129 ]. This software was selected because of its capacity to efficiently manage network visualization tasks by combining text mining algorithms with visualizations. This section provides an in-depth explanation of the method applied.

2.1 Database and search keywords selection

From Scopus, we collected all publications dealing with TikTok. This database represents one of the most extensive libraries of abstracts and citations of peer-reviewed materials including numerous conference proceedings and journal articles [ 128 ]. Researchers regularly use Scopus to achieve high-quality analyses due to its substantial collection of scholarly literature and its many user-friendly features that simplify the execution of bibliometric analyses [ 50 ]. Scopus boasts a broader and more inclusive database in comparison to both Web of Science (WoS) and PubMed. To illustrate, while Scopus encompasses almost 85% of the publications indexed in WoS, only 54% of Scopus’ own documents can be found within the WoS database [ 55 ]. This also demonstrates our commitment to attaining a comprehensive view of the subject matter, in line with our research objectives. Data related to authors, journals, publication type, titles, abstracts, keywords, and publications’ numbers were collected. Extracted data were exported to a CSV file for use in further analyses. The following search query was used in the title, abstract, and keywords fields to retrieve publications from the Scopus database: TikTok OR Douyin. These keywords were chosen based on their direct relevance to the research subject. TikTok represents the global brand, while Douyin is its Chinese counterpart. The inclusion of both terms ensures that we capture all relevant research, regardless of regional focus. Given their status as authoritative sources [ 109 ], we limited our search to English-language journal articles and reviews. On January 22, 2023, a search was performed, and 550 documents were found. The next step was to determine whether articles were relevant to the topic at hand by reviewing their titles and abstracts; this process resulted in the removal of 8 articles. As a result, a total of 542 publications were selected.

2.2 Preliminary data analysis

We retrieved the BibTex format of all articles’ metadata, including the titles, abstracts, keywords, and authors. Table 1 presents the main information about the selected set. The data in the table indicates a collaboration index of 3.3. Ajiferuke et al. [ 2 ] developed the collaboration index, representing a novel measure of fractional productivity, which quantifies the extent of collaboration among the authors of the scholarly articles. The selection of this index was motivated by the need to better understand the nature of collaboration in the research field under study. A low value for this index suggests that articles produced by single authors prevail, thus shedding light on the dynamics of individual vs. collective research within the selected dataset. This insight helps in characterizing the research landscape and in understanding collaboration patterns. Scholars undertaking meta-analytic studies argue about the types of publications included in the analysis. For example, Aryadoust and Ang [ 8 ] relied on books and journal articles in their study, while Della Corte et al. [ 155 ] relied entirely on journal articles. In this study, only peer-reviewed journal articles were considered for the analysis.

2.3 Network analysis

Incorporating elements of statistics, mathematics, and computer science, social network analysis (SNA) has rapidly developed into a rigorous analysis method. Using a network-based approach to synthesis, the SNA method can reveal previously hidden connections between publications, which can aid theory building and point the way toward promising new research avenues [ 33 , 70 ]. Although several statistical measures have been developed for analyzing networks, the scope of this research focuses on the three most basic: network size, network diameter, and network density. SNA methods have been widely used in the academic literature. For example, co-citation networks have been the subject of prior research [ 58 , 127 ]. Li et al. [ 80 ] state that the knowledge foundation and development of a given research field can be observed through the co-citation network, which symbolizes a knowledge network consisting of two articles concurrently referenced in a third article. In addition, co-citation networks can be used to evaluate the degree to which two articles or authors share a common research interest. Changes in academic domains can be uncovered by analyzing co-citation patterns over time [ 7 , 27 ]. Moreover, the structure of a research domain can be illustrated by the generation of source co-citation networks [ 25 , 36 ]. According to Wakefield [ 132 ], source co-citation can graphically show the knowledge trends that suggest commonalities among academic journals, including research focus or methodology. Finally, a number of bibliometric analyses make extensive use of collaborative networks [ 94 ]. Collaboration networks are a useful bibliometric tool that can be visualized as a graph with nodes representing authors, nations, or academic institutions and links between nodes representing co-authorships between authors, nations, or academic institutions. In particular, it was shown collaborative efforts among researchers could create reciprocal advantages, boost research innovation and information diffusion, and improve the quality of research output [ 111 ]. In the same vein, Glänzel and Schubert [ 57 ] find that multi-authored works are more likely to appear in high-profile journals and receive a higher number of citations than those produced by a single researcher. As Ding [ 43 ] demonstrates further, inter-university collaboration can lead to fruitful research collaborations that ultimately aid in policy development. Furthermore, the analysis of the keyword co-occurrence network enables researchers to detect signal words or major thematic areas covered in a specific knowledge domain [ 123 ]. A keyword co-occurrence network is also a useful data mining approach that helps scholars reveal the main streams of inquiry that have contributed to the formation of TikTok research [ 146 , 147 ]. Each network node stands for a keyword, and its color indicates which cluster it belongs. Nodes are larger when the keyword occurs more often, and relationships between nodes are stronger when the edges connecting them are thicker.

2.4 Thematic and conceptual structure analysis

Strategic or thematic maps are built upon the metrics of centrality and density established by Law et al. [ 79 ]. Researchers can use the maps to examine how recurring keyword patterns reveal emerging themes [ 77 , 95 ]. The approaches employed to generate these maps have been inspired from both financial portfolio analysis and co-word networks [ 151 ]. The power of the thematic map rests on its capacity to distinguish the density and centrality of research within a number of categories [ 77 ]. While centrality represents the breadth of connection between topics, density reveals the progress of a theme [ 49 ]. The thematic map, which is created by clustering together frequently used keywords, provides more objective insights than the conceptual structure map. The use of a thematic map facilitates the rapid and straightforward identification of core themes and lays the foundation for further research into the various categories to which themes are subsequently ascribed [ 68 ]. Several studies in the academic literature have employed thematic maps [ 77 , 95 ]. Besides thematic maps, conceptual structure maps are another way of knowledge visualization. These maps are useful for segmenting a broad scientific domain into more manageable study subfields. Keywords are represented as dots on a map, and results are displayed in accordance with the locations of those dots. Closer dots indicate that there are more publications addressing the concepts or ideas together, while dots that are farther apart suggest a lesser number of articles discussing the topics [ 35 ]. Therefore, this allows for the detection of keyword citation bursts or new research trends [ 31 ]. As such, it is feasible to understand better which knowledge hotspots often arise in the academic literature.

3.1 Scholarly output, key journals, and productive authors

We first trace the history of TikTok research and its progress. The number of articles dealing with TikTok is shown in Fig. 1 . The chart shows that the number of articles published each year has increased exponentially. In 2019, only three articles were published, but the number of articles grew more than tenfold in 2020. In fact, TikTok’s rise to prominence in 2020 coincided with the COVID-19 pandemic that swept the globe, but the app has a long and storied history spanning numerous incarnations. Zhang Yiming launched the company ByteDance in 2012, and in 2016, the company released the app Douyin in China, which enables users to produce and share short clips of themselves. Simultaneously, another app called Musical.ly [ 5 ] emerged from China with a similar idea but a concentration on lip-syncing and dancing. In 2015, Musical.ly surpassed Douyin to become the most downloaded app in the United States. ByteDance, on the other hand, built an algorithm that took into consideration the kinds of videos a user uploaded, shared, liked, disliked, and commented on, as well as the accounts the user chose to follow. ByteDance, which had previously acquired Musical.ly, integrated Musical.ly with Douyin and relaunched it as the worldwide app TikTok in 2018 [ 72 ]. Overall, the annual number of articles has increased significantly over the past two years. This finding is highly meaningful and significant in bibliometrics since the field had an immature base of publications from the start, witnessed tremendous expansion, and greatly influenced the academic world. Consistent with Price [ 104 ], it is expected that TikTok research will enter its vigorous growth phase as the number of publications has grown exponentially over time, and the vast majority of the literature has been published in the past few years. We can speculate that the meteoric rise of TikTok research has only begun, and it will soon have profound effects on science and technology.

Annual distribution of TikTok-related publications

A wordcloud of the most influential journals that have published scholarly articles on TikTok is shown in Fig. 2 . The wordcloud is used to showcase the most prominent outlets in the TikTok field, with the size of the label reflecting the total number of citations each journal has received. According to the chart, journals such as International Journal of Environmental Research and Public, Health in Psychology, Social Media and Society, Journal of Medical Internet Research, Media and Communication, and Frontiers of Public Health stand out as the most impactful journals in TikTok research. Overall, we observe that health journals dominate the journal distribution in TikTok research.

Main influential journals in TikTok research

Academic journal productivity can be evaluated using the Bradford law. The law arises from the need to track down the main journals that have published articles on the subject at hand during the course of a research period [ 24 ]. The law states that “if scientific journals are arranged in order of decreasing productivity of articles on a given subject, they may be divided into a nucleus of periodicals more particularly devoted to the subject and several groups or zones containing the same number of articles as the nucleus [ 20 ]”. The Bradford law in the TikTok literature is depicted in Fig. 3 . Using R-Biblioshiny to apply Bradford law, the inverse connection of Bradford [ 20 ] is immediately apparent since the first zone of the graph illustrates the core zone or Bradford zone 1. This zone comprises a handful of academic (40 out of 365) journals such as International Journal of Environmental Research, Frontiers in Psychology, Social Media and Society, and Journal of Medical Internet Research. This shows that the bulk of TikTok-related publications is published mainly in eight different outlets.

Bradford’s law in TikTok research

Based on the data from the Scopus database, Fig. 4 depicts the dominance of authors in TikTok research throughout time. From 2020 to 2021, Sidorenko-Bautista, P. ruled, and from 2021 to 2022, Basch, C.H. and Fera, J. predominated.

Top authors in TikTok research over time

In the present study, Lotka’s law is applied to assess the relative importance of each TikTok contributor [ 101 ]. According to the law, the authors are ranked by their number of articles, then the total number of authors should be proportional to 1/n2 [ 145 ]. In a nutshell, Lotka’s law states that the number of authors negatively correlates with the number of publications each author contributes to the literature [ 76 ]. With the help of bibliometrix R-package, we were able to apply Lotka’s law to TikTok research. The Lotka’s distribution is depicted in Fig. 5 . The Kolmogorov-Smirnov two-sample test shows no statistically significant differences between the empirical and theoretical distributions at the standard 0.05 level of significance. Furthermore, the long tail for authors with a single publication in Fig. 5 suggests that some researchers have looked into TikTok as a subordinate research topic. Overall, the results suggest that Lotka’s law is valid for TikTok-related publications. This pattern of results is also observed in other study fields [ 94 ].

Lotka’s law in TikTok research

3.2 Analysis of networks

3.2.1 collaboration networks analysis.

The collaboration networks among authors and institutions in TikTok research were obtained through the following steps using the Bibliometrix software: 1) Data Collection: Compilation of metadata, including authors and institutions; 2) Network Construction: Creation of an authors’ collaboration network and an institutional collaboration network based on the relationships identified in the data; 3) Network Analysis: Computation of network parameters such as size, density, and diameter for detailed analysis; 4) Visualization: Rendering the networks into graphical form, with interrelated research communities depicted in different colors in Fig. 6 , and institutional collaboration shown in Fig. 7 . The authors’ collaboration network in TikTok research is shown in Fig. 6 . The size of the network is 1647, with a density of 0.0024 and a diameter of 4. A few interrelated research communities are depicted in the graphic, each represented by a different color. The pieces of the network are fragmented, indicating that the most influential academics prefer to work independently. The participation of islands disconnected from the rest of the academic community is further supported by previous studies (e.g., [ 74 ]).

Authors’ collaboration network in TikTok research

Institutional collaboration network in TikTok research

Figure 7 illustrates the network of institutional collaboration in TikTok research, with a size of 804, a density of 0.0038, and a diameter of 19. There is limited collaboration between the institutions in the network. The University of Southern California, Yale School of Medicine, and University of Pennsylvania, for example, cooperate together often. Zou et al. [ 153 ] coined the term “locally-centralized globally discrete” to describe this type of collaboration. Even though there is a strong research collaboration among US and Chinese universities, there is much less cooperation between academic institutions in developing and developed nations, reflecting a North-South divide. Intriguingly, geographic proximity and language may be the major reasons of collaboration in TikTok research.

3.2.2 Keywords and co-occurrence analyses

Keywords have been commonly used in the academic literature to identify essential information and subject trends despite their high level of abstraction [ 111 ]. Figure 8 is a wordcloud containing terms taken from the abstracts of papers dealing with TikTok. A close glance at the chart reveals that the keywords “TikTok,” “social media,” “video,” “platform,” “content,” and “health,” are among the most frequently used search terms.

Wordcloud of the most used keywords in the articles’ abstracts

Using keyword plus, Fig. 9 displays the dynamics of keyword growth. Sharp increases in keywords’ popularity reveal priorities and trends in TikTok research. COVID-19, Instagram, China, adolescents, and public health are all examples of relevant search terms. Since the body of knowledge in a certain academic discipline can be seen as a chain of ideas that develop, become more prominent for a while, and then fade away, these keywords also represent possible new directions or hotspots in TikTok research [ 32 ].

Keywords’ growth dynamics in TikTok research

Using the Bibliometrix software, we generated a keyword co-occurrence network in six steps: 1) Data Collection: We extracted all the keywords from the selected publications; 2) Keyword Frequency Analysis: We identified and selected the top 69 most frequent keywords; 3) Network Construction: Using the selected keywords, we constructed a network, mapping the co-occurrences between them; 4) Network Analysis: We analyzed the network to determine important parameters such as size, density, and diameter; 5) Cluster Identification: Through advanced algorithms, we identified five distinct clusters within the network, representing different thematic areas of focus; 6) Visualization: We used Bibliometrix's visualization tools to render the network into Fig. 10 , using a size, density, and diameter of 1574, 0.0055, and 6, respectively. The figure depicts the five distinct clusters and highlights key thematic areas within the research landscape.

Keyword co-occurrence network in TikTok research

As can be seen from the map, the red cluster near the center of the network has the most impact. The focus of this cluster is on the relationship between TikTok, COVID-19, and public health. COVID-19, public health, tics, health information, mental health, tobacco, and vaping are all semantically related keywords. According to Reuter et al. [ 112 ], public health organizations have embraced social media platforms like TikTok for health promotion to heighten public understanding of health risks and inspire beneficial alterations in behavior. TikTok can be used to broadcast information and educate the public on issues including COVID-19 prevention [ 26 , 122 ], mental health [ 30 , 88 ], and healthy lifestyles [ 103 ]. In their recent study, Li et al. [ 82 ] argue that the widespread popularity of the handwashing dance on TikTok implies that such videos can be used to illustrate and, hopefully, encourage healthy practices like washing hands, wearing face masks, and maintaining a safe distance from others. The authors also find that TikTok videos containing risk information related to COVID-19 and the response efficacy of preventive measures have increased user engagement. Despite its potential for public health, TikTok is also known for spreading misinformation, disinformation, and conspiracy theories, especially concerning the COVID-19 pandemic [ 5 ]. The platform can also lead to the development of tics that differ from those experienced in people with Tourette syndrome but share several features with functional tics. According to Olvera et al. [ 97 ], these tics represent an instance of mass sociogenic sickness, in which emotions, conditions, and behaviors spread unintentionally across a population. Moreover, TikTok has been associated with the use of tobacco and vaping products. According to Rutherford et al. [ 115 ], the popularity of pro-e-cigarette usage and vaping-related material has been confirmed by recent content analyses of TikTok. This is despite the fact that many online communities include rules against discussing, displaying, or trading illegal substances such as alcohol, tobacco products, and drugs [ 115 ]. Purushothaman et al. [ 106 ] state that TikTok has been linked to the dissemination of pro-smoking and pro-tobacco product rhetoric. As a result, exposure to TikTok content can lead to the normalization of tobacco use and a higher willingness to engage in vaping practices [ 14 , 93 , 115 , 125 ].

The second cluster is related to alternative social media platforms and their association with health communication and education. For example, Reuter et al. [ 112 ] highlight that Instagram distinguishes out as a platform that prioritizes visual material over text, thus having more the potential to affect users’ inclination to interact with health messages. Al-Maroof et al. [ 4 ] observe that in contrast to TikTok, YouTube significantly impacts viewers’ medical understanding and perception. While TikTok was created to facilitate self-expression and socialization, YouTube has a wide range of education and non-educational uses thanks to its flexibility in terms of both the content and scheduling of videos posted there. When it comes to the field of dermatology, Cooper et al. [ 34 ] posit that Twitter has surpassed all other social media platforms as the preferred means for healthcare communication. Twitter facilitates public discussion about skin conditions, which raises awareness of skin diseases, provides a secure environment for patients, and offers emotional and social support [ 37 ]. The collaborative features of Facebook have also attracted organizations and audiences interested in dermatology-related material and healthcare advice [ 126 ]. The high frequency of the keywords deep learning and AI indicates the importance of these technologies in developing content analysis models for studying TikTok and social media content [ 54 , 62 , 143 ].

The third green cluster focuses on TikTok research from the Chinese perspective. Most frequent keywords in the cluster include China, algorithms, platform governance, geopolitics, and identity. While the algorithms behind the information that is organized, ranked and picked for people’s feeds are often secret and black boxes, they are made evident in social media users’ online experiences. In this respect, algorithms function as a knowledge system about the problem(s) they are designed to address, and as such, they cannot be said to be decoupled from the environment in which they are implemented [ 56 ]. Unlike other popular social media platforms, TikTok’s success does not rely as much on users’ ability to interact with one another. Instead, the platform generates a never-ending supply of short videos by largely relying on algorithms, user behavior, and AI learning capabilities [ 9 ]. Although TikTok has taken a distinct de-sinicization strategy by trying to downplay or hide its ties to China and the Chinese government, the platform has become the major line of discourse for critics, investigators, and ban advocates [ 91 ]. The algorithmic-driven content moderation has raised concerns about platform governance, which has been shaped by geopolitics [ 59 ] and users’ identity [ 71 ]. For example, Wang and Zhou [ 133 ] note that TikTok, through its algorithms, has punished content deemed unsavory, such as videos made by members of the LGBTQ community, creators with visible disabilities, obesity, or unattractive faces. Zeng and Kaye et al. [ 72 ] state that some of the issues faced by TikTok are attributed to geopolitics, particularly the network’s Chinese origins and the inability to regulate the content posted on the platform. As a result, this illustrates the intricate relationship between TikTok, politics, and identity.

The fourth cluster (purple-colored) concentrates on several aspects of social networks, including body image, uses and gratifications (U and G), motivation, personality traits, and self-esteem. Related to this theme, Pop et al. [ 102 ] find that students’ feelings about their body esteem improved in proportion to the amount of time spent on TikTok and Snapchat. Holland and Tiggemann [ 66 ] conduct a literature review analyzing twenty studies on social network use and body image and find a correlation between body image indices and overall social network use. Pan et al. [ 100 ] establish that exposure to social media influencers is associated with a desire to alter one’s physical appearance. From the perspective of uses and gratifications theory, several studies in the cluster investigate the impact of personality traits and motivations on the use of TikTok. For example, Omar and Dequan [ 98 ] indicate that self-expression, archiving, escapism, and social interaction are major predictors of TikTok use patterns, although to varying degrees and effects. Meng and Leung [ 89 ] look at how personality traits, narcissism, and gratifications-sought influence TikTok engagement behavior in China. Their findings show different gratifications sought, including fashion, escape, information seeking, entertainment, sociability seeking, money making, modality, and interactivity. Overall, the focus of the cluster is on the motives and gratifications of using social network sites.

Finally, the orange cluster emphasizes the popularity of TikTok among children and students. Given that these groups remain the major demographic involved in TikTok use, they are subject to serious predators, ranging from radicals, terrorists, and cyber-attackers, to criminals. In this vein, Weimann and Masri [ 136 ] report that the content of far-right groups has recently increased on TikTok, exposing children to hate, offense, and animosity. Similarly, De Leyn et al. [ 38 ] stress that concerns regarding children’s privacy on TikTok have been sparked by the exponential popularity of the app. As a result, there is a need for effective privacy management to promote self-representation practices and the protection of sensitive data [ 19 ].

3.3 Topic modeling approach

Since abstracts are widely accepted as reflecting the essential content of publications, topic modeling was used for the abstracts of selected articles to obtain a more in-depth knowledge of the primary topics discussed in TikTok research. In the context of machine learning, topic modeling is a strategy that looks for word use patterns and gives common terms new meanings by grouping them together [ 60 ]. The use of topic modeling enables streamlining the analysis of large amounts of unlabeled texts by grouping words with similar meanings together and distinguishing how words with multiple meanings are used [ 152 ]. Generally, it is common practice to use topic modeling to unearth latent themes or topics in a collection of texts or corpus. This technique views each theme in a given text as a composite of several topics. In the current work, the Latent Dirichlet Allocation (LDA) approach was applied to reveal the latent topics concealed within the abstracts of the selected TikTok-related publications. This method has been used extensively in research analyzing Industry 4.0, the public sentiment and opinion during the COVID-19 crisis, and international trade [ 69 , 78 , 142 ]. First, we did some text preparation to improve the overall quality of the collected data. More specifically, we employed tokenization to split abstracts into word units and normalization to convert all capital letters to lowercase ones. Words with inflected forms were diminished via the use of stemming. Due to their lack of useful information, stop words, punctuations, and numbers were also removed [ 116 ]. As can be seen in Fig. 11 , the LDA approaches yielded six overarching themes in TikTok research. In this figure, the vertical axis displays the keywords representing different themes, while the horizontal axis shows the values of beta, which signifies the relevance of each keyword to the corresponding theme.

Topic modeling in TikTok research applying the LDA technique

The first theme deals mostly with the privacy issues associated with TikTok use. Despite users’ enjoyment of using TikTok, there are rising worries about the origins of the application and its possible privacy infractions. For example, Donald Trump, the former President of the United States, has stated a wish to prevent TikTok from being available in US app stores, including Apple’s App Store and Google’s Play Store [ 73 ]. Miao et al. [ 91 ] note that the Chinese origin of TikTok has led to the assumption that Internet companies in China are often subject to strong government surveillance and, as a result, are likely to communicate user data to the Chinese government, putting user privacy and potentially national security at risk in countries in which they operate. As a networked public, the dynamics of TikTok raise worries about children’s safety due to the difficulties presented by safeguarding privacy on this platform and the presumptive predisposition of youth for irresponsible exposure [ 38 ]. Therefore, privacy and data protection represent one of the greatest challenges for the overseas expansion of TikTok, which requires the reorganization of the operations and governance structure of the company behind TikTok. The second topic revolves around TikTok use in education. Because of its popularity among adolescents, TikTok can effectively reach young people with messages on education and health [ 52 ]. For instance, Escamilla-Fajardo et al. [ 48 ] demonstrate that there have been beneficial educational results from using TikTok’s innovative approach to teaching. According to the authors, students felt using TikTok encouraged their imaginative and inventive abilities. Sari et al. [ 117 ] note that teachers in the field of physical education can leverage the video-sharing platform TikTok to explain movement concepts to their students and recap their learning activities. TikTok can be easily used to modernize education, increase outreach, and improve students' creativity and communication skills.

The third topic is related to the analysis of media news on TikTok. In this regard, Vázquez-Herrero et al. [ 131 ] perform a content analysis of 19 news media and programs with a verified profile and broad thematic scope after selecting 234 accounts based on an exploratory search of news media on TikTok across the globe. According to the findings, the media has been more included in the younger generation’s news diet since 2019, with the goals of informing, establishing their brand, and adjusting to TikTok logic in a novel approach to journalism for the youth of today. Despite the influence and prevalence of TikTok, few TV news outlets are willing to take plunge and attempt to get TikTok users to switch to traditional news broadcasts. In their study, Chobanyan and Nikolskaya [ 29 ] assess the current landscape of TikTok news players and the app’s potential to become a second major news outlet by analyzing the two popular NBC News and CBS News Channels on TikTok. Although young people stress the need for entertainment and brevity in any prospective TV news videos on TikTok, the research demonstrates that even serious and least enjoyable videos can acquire millions of views and likes. The fourth theme deals with the characteristics of COVID-19-related content posted on TikTok. The emergence of the COVID-19 pandemic has been instrumental in TikTok’s meteoric rise, and the platform played a crucial role in disseminating factual and erroneous information regarding the pandemic [ 5 , 99 ]. The fifth topic deals with the characteristics of TikTok videos, including video quality, views, comments, likes, and comments. When applied to various video-based platforms like TikTok, the DISCERN instrument has been shown to be an effective tool for evaluating the reliability and quality of textual patient health information about treatment options [ 11 , 83 ]. Finally, the sixth topic discusses the use of TikTok short videos to support brands and reach consumers.

3.4 Multiple correspondence and thematic analyses

Multiple correspondence analysis (MCA) was used to investigate the conceptual structure of TikTok research. MCA was employed to construct the conceptual structure map in the R-Bibliometrix software by examining the keywords’ proximity in the selected publications [ 40 ]. On the map, distributionally similar terms appear closer together [ 92 ]. In addition, we used the conceptualStructure function in R to obtain the authors’ keywords. Taking into account the similarity of the keywords in the map, we also used k-means clustering to generate clusters with shared ideas [ 111 ]. K-means is often used for clustering, and when combined with MCA, a two-dimensional graphic is produced showing the most important keywords, their connections, and new trends and directions in the knowledge area. The conceptual structure map of TikTok-related scholarly articles is shown in Fig. 12 . The graphic depicts four different clusters for the intellectual structure of TikTok research. The red cluster includes keywords that focus on three critical aspects of TikTok: information quality, use and gratification, and platformization. Information quality, misinformation, U and G (use and gratification), platform governance, and platformization are just a few examples. Related articles include Qin et al. [ 107 ], who find that information quality has a significant effect on enjoyment. Similarly, Song et al. [ 120 ] conclude that TikTok videos about the chronic obstructive pulmonary disease (COPD) have a generally satisfactory information quality even though the quality differs according to the source and the quality metric used. As a result, TikTok faces challenges in ensuring information quality and combating the spread of misinformation. Similar to other social media platforms, TikTok also offers users a variety of ways to satisfy their needs and desires through the platform. In this context, Bucknell Bossen and Kottasz [ 23 ] investigate the uses and gratifications desired by the major audience (pre-adolescent and teenage groups) of TikTok and find that users’ behaviors are driven by the need to broaden one’s social circle as well as by the desire for self-expression, celebrity, and a sense of self-identity. Drawing on the approach of uses and gratifications, Scherr and Wang [ 119 ] examine TikTok’s gratification niches and find that the app is used for four reasons: trendiness, novelty, escapist addiction, and socially rewarding self-presentation. Omar and Dequan [ 98 ] find that TikTok use is significantly influenced by individuals’ motives rather than their personality traits. Users’ motives, such as social interaction, self-expression, and escapism, are also identified as significant predictors of TikTok use behavior. As a product of the process of platformization, there is a need for TikTok to maintain the safety and well-being of users, protect privacy, and guarantee the quality and accuracy of the information shared on the platform. The second cluster in green contains keywords such as public health, body image, children, and adolescents. This cluster focuses on the impact of TikTok on public health and body image. Representative articles include Southwick et al. [ 122 ], who confirm the importance of TikTok video analysis in informing public health messaging and public health mitigation policies; Basch et al. [ 15 ], who conduct a cross-sectional research to explore how users of the video sharing platform TikTok are discussing a key component of community mitigation—the usage of masks to prevent the spread of COVID-19; and Brooks et al. [ 21 ], who highlight the negative impact of TikTok as an emerging platform for the promotion of unhealthy eating. Besides public health, TikTok can impact how users perceive their bodies and body image. For example, Pop et al. [ 102 ] show that the more time students spend on social media platforms like Snapchat and TikTok, the higher their self-esteem. Pan et al. [ 100 ] demonstrate that the connection between female TikTokers’ exposure to influencers and their desire to alter their physical appearance is mediated by their self-objectification. The final cluster includes various examples of social media platforms, including YouTube, Facebook, Instagram, and Twitter. When compared to Twitter and Facebook, where users’ feeds are dominated by posts from their friends and followers, the feed of TikTok is similar to Instagram’s “Discover” feature, with almost all of its users’ time is spent within the app itself [ 53 ].

Conceptual structure map of TikTok research

The thematic map of TikTok research is depicted in Fig. 13 . The number of occurrences of each keyword in the selected articles is represented by the size of the bubbles. Cobo et al. [ 31 ] state that the motor themes quadrant has very dense and central themes that are both externally and internally developed. The niche themes quadrant contains all topics that are strongly interconnected internally but have only weak exterior links. The literature also characterizes such topics as unique and elaborate. All the themes that are low in density and centrality and have few connections to other themes fall into the quadrant of emerging or declining themes. The basic themes quadrant is characterized by high centrality and low density. It contains themes with significant external linkages and weak internal linkages. Therefore, the first upper-right quadrant contains themes with both high centrality and density. The topics discussed in this section of the research map are well-established and have the potential to shape the development of the knowledge field. As a result, themes associated with Instagram, YouTube, Twitter, Facebook, and influencers have remained fundamental and prevalent over the few years of TikTok research development and growth.

Thematic map of TikTok research

In contrast, themes related to social media and TikTok use in the COVID-19 context are characterized by high centrality and low density, suggesting that while they can influence other themes, they are not fully developed and may shed light on future knowledge gaps. In the upper-left quadrant, keywords like social network, children, body image, internet, and engagement indicate that the impact of social networks (e.g., TikTok) on children’s body image and engagement is a niche theme in TikTok research. This theme is well-developed in terms of internal linkages but has weak external connections and low importance. Finally, keywords located in the lower-left quadrant, like China, algorithms, gender, and mobile apps, are examples of nascent and poorly developed topics

4 Discussion and future research

The progression of TikTok research from its inception reveals a fascinating panorama of technological, cultural, and academic convergence. Starting with a modest three articles in 2019, the field saw an explosive growth in 2020, corresponding with the global upheaval of the COVID-19 pandemic. This synchronicity between real-world urgency and academic response extends beyond mere coincidence, signifying a broader shift in scholarly focus towards digital platforms. The platform’s historical lineage, with roots in Douyin and Musical.ly , underlines the importance of recognizing digital phenomena as part of a longer continuum rather than isolated events. Moreover, the critical role of ByteDance’s algorithm brings to light the complex interplay between technology and content, raising essential questions about user agency and data privacy. Looking ahead, the current exponential growth in TikTok research may lead to more specialized niches, reflecting the platform’s multifaceted applications in politics, public health, and entertainment. This trajectory emphasizes that while digital platforms may seem transient, their profound effects on culture, society, and academia warrant enduring scholarly exploration.

The research status related to TikTok has evolved to encompass diverse domains, highlighting several emerging and prevalent hotspots. One of the dominant research focuses is on TikTok’s impact on public health. There is evidence that TikTok has great potential as a platform for distributing public health information, especially in areas like pandemic information, mental health, eating disorders, and well-being among children [ 16 , 88 ]. Concurrently, researchers are exploring TikTok’s collaboration with public health professionals during the COVID-19 pandemic, its improvement of user experience among the younger generation, and how it could be utilized by healthcare organizations for patient communication [ 82 , 120 ]. The possibility of TikTok as a tool for telemedicine and remote health consultation is also emerging as an important area. Additionally, understanding the interplay between user identity and algorithmic processes on TikTok has been recognized as significant, exploring how TikTok’s algorithms contribute to misinformation or the formation of echo chambers [ 10 , 12 ]. Furthermore, the research also emphasizes the importance of understanding TikTok’s effects on body image, considering the platform’s popularity and user engagement. Substantial research has been conducted on TikTok in China, particularly from the perspective of algorithms, platform governance, and geopolitics. This includes exploring how the Chinese government employs TikTok for online activity monitoring and control. These hotspots represent the central themes that are shaping the current state of TikTok-related research, suggesting that academic inquiry into this platform is multifaceted and growing in complexity, with significant potential for further exploration in both well-established and emergent areas.

The prominence of authors such as Sidorenko-Bautista, P., Basch, C.H., and Fera, J. in the TikTok research field between 2020 and 2022 suggests more than just a measure of productivity or influence. It hints at possible underlying trends or shifts in research focus that may correspond to their areas of expertise. Are these authors pioneering new methodologies or unearthing specific insights that are driving the field forward? Their prominence could be a reflection of the evolving nature of TikTok itself, a platform that has rapidly changed and expanded since its inception. It would be valuable to explore how these authors' works align with or diverge from the overall trajectory of TikTok’s development.

Regarding collaboration among scholars and institutions, the data paints a picture of fragmentation and localized focus. While the low density of collaboration among authors could be seen as a lack of cohesive direction in TikTok research, it might also be indicative of a young and still emerging field. Individual scholars might be carving out unique niches or exploring disparate questions that do not lend themselves to broad collaboration. On an institutional level, the localized collaboration and the North-South divide may reveal underlying socio-political or economic factors that shape research collaboration. It might also expose a lack of standardized frameworks or common goals that would facilitate more extensive global collaboration. The role of geographic proximity and language in driving these trends could reflect both the practicalities of research collaboration and the cultural or regional specificity of TikTok as a subject of study. The platform’s variable impact and usage across different contexts might necessitate localized study, thus explaining the observed patterns.

This study suggests several future research directions based on the analysis of the keyword co-occurrence network and topic modeling:

Future studies should thoroughly investigate the impact of TikTok on mental health and well-being, especially among children [ 39 ]. Health-harming product advertising, hateful content spread, misinformation, illness portrayal, and excessive use or addiction are all areas that need further attention from researchers [ 99 ]. Furthermore, qualitative studies on TikTok users to better comprehend how TikTok videos impact the understanding of pandemics and promote public health practices, including vaccination, social distancing, and face mask-wearing, are necessary [ 122 ]. Researchers should also study how tobacco-related content on TikTok can influence young people’s perception of smoking and their propensity to try cigars and vapes for the first time [ 139 ]. The analysis of the effects of TikTok on physical health, including eating disorders [ 65 ], sleep patterns [ 19 ], and sedentary behavior [ 63 ] is encouraged for future research.

Future research should explore the use of TikTok by healthcare organizations and professionals to communicate with patients and the public. Best practice guidelines for professionals wishing to use TikTok to convey critical and impactful health information can be improved with the help of additional multidisciplinary studies that combine data science techniques for qualitative data collection and clinical interpretation [ 88 ]. Future researchers are recommended to identify what strategies can increase user engagement in health information and education [ 67 ]. A pending research question is how algorithms and personalization can impact health information seeking and sharing on TikTok. In addition, increased attention is required to devise methods for applying the features of widely viewed videos to messages about public health. This is crucial for empowering individuals to make educated decisions about disease prevention and health promotion [ 14 , 15 ]. Lastly, researchers should evaluate the potential of TikTok as a tool for telemedicine and remote health consultation.

Substantial research has been conducted on China from the perspective of algorithms, platform governance, and geopolitics. In the future, researchers should focus on understanding how TikTok can shape public opinion and impact domestic and international politics. In addition, scholars may investigate how the Chinese government employs TikTok to monitor and control online activity and content. Related to algorithms, Karizat et al. [ 71 ] argue that there is little understanding of the interplay between user identity and algorithmic processes on TikTok. Therefore, there is a need to clarify how such understanding shapes user behavior on the platform. Researchers should strive to explain how TikTok recommendation algorithms operate and how they influence information dissemination and online communities' development [ 10 ]. Another interesting avenue is to explore how TikTok’s algorithms can contribute to misinformation or the formation of echo chambers [ 12 ]. Since the platform governance of TikTok has been under criticism and strict scrutiny [ 148 ], future studies may examine the ability of TikTok to moderate the enormous amount of content posted and employ algorithms to promote or demote certain types of content. As algorithmic content moderation becomes the norm, online platforms are ruled more by mathematical statistics, which may lead to human costs and mistakes. Research in the future should concentrate on the individuals bearing the responsibilities and the cost. Concerns associated with visibility moderation on TikTok are not amenable to straightforward solutions or quick escapes. As a result, visibility moderation can be researched further to educate academic discussions, provide policy suggestions, and impact public dialogue regarding TikTok governance.

Given the fast growth of TikTok and the great level of user engagement, a closer look at the impacts of TikTok use on body image is necessary. Users of TikTok can be at greater risk of being exposed to idealized body images because of the growing interest in short video apps and the high intensity with which users interact with them. However, TikTok and similar apps enable users to modify or filter their short videos to show an idealized body image. Despite the fact that TikTok may have similar detrimental impacts as Instagram and Facebook, there has been surprisingly little research concentrating on this platform's effects on body image. In addition, it is insightful to examine the role of TikTok algorithms in shaping body image and self-esteem and how these perceptions may differ from those formed through traditional media. Researchers can also investigate the influence of TikTok use in the context of other aspects, including physical activity [ 19 , 63 ], nutrition [ 52 ], and overall well-being. Finally, comparing the impact of TikTok use and other social media platforms on the body images of people is another promising research direction.

5 Conclusion and limitations

This study aimed to investigate the scope and knowledge structure of TikTok research over recent years. Using bibliometric approaches, 542 articles written by 1535 authors were thoroughly examined. Unlike subjective approaches (e.g., systematic literature reviews), bibliometric approaches can objectively map a whole research field since a random selection of evidence is not wholly representative of the present state of research and favoring some articles over others introduces bias into the analysis. Thus, the use of bibliometrics can reveal the broad landscape of TikTok-related publications. To the best of the authors’ knowledge, this study represents the first attempt to explore the bibliometric structure of TikTok research. In this comprehensive study, we uncovered the relevant trends, the most prolific scholars, and the leading journals in the TikTok field. In particular, we found that most of the networks analyzed have a hub-and-spoke design [ 135 ]. As a result, a few productive scholars and academic institutions seem to drive TikTok research forward. Such academics or institutions can be thought as information brokers (i.e., conduits of knowledge) [ 113 ].

Interestingly, geographical proximity and cultural affinity have influenced the research cooperation between countries and academic institutions. This finding aligns with the conclusions of several researchers who analyzed the patterns of collaboration between scholars [ 105 ]. In line with past studies, we find that universities are the main source of publications dealing with TikTok, followed by research institutions like National Opinion Research Center, Chicago and Westat, Inc. Additionally, insufficient collaboration between developing and developed nations in TikTok research was observed in other scientific domains [ 130 ]. Concerning the TikTok field's conceptual structure, the keyword co-occurrence network and topic modeling analysis indicates that public health, health education and communication, algorithms, platform governance, and body image receive significant attention from scholars. In other words, TikTok has the potential to impact public health, convey critical health messages, algorithmically drive user experience, and shape body image perception. Scholars also place emphasis on the impact of TikTok use on children, students, and brands.

A number of insights and implications can be drawn from this study for both academics and practitioners. This article presents a comprehensive bibliometric analysis that pinpoints, organizes, and examines key aspects of TikTok research and highlights the need for further investigations. The current article objectively reveals the research performance results related to TikTok by highlighting the most productive authors, journals, countries, institutions, and main topics. The review deepens the practitioners’ understanding of the fundamental concepts explored in the TikTok-related literature and adds to its historical development. Researchers may use the study’s findings to learn more about the global scope and distribution of TikTok research among authors, publication outlets, countries, and academic institutions. In addition, it helps academics understand the history, evolution, and present state of TikTok research and pick out the most important trends and future research directions.

This study has certain limitations. First, using only the Scopus database may have affected the findings, potentially leading to a bias in the representation of the field, since the choice of database can influence the scope and direction of research findings. Future research may extend our findings by using other scientific databases such as the WoS and contrasting the findings with the results of this study to mitigate any bias stemming from database selection. Second, although methods such as topic modeling enable coverage of a wide variety of publications, they still cannot match human reviewers’ accuracy when analyzing and interpreting content. This limitation might introduce bias in theme detection and interpretation. Through the use of keyword frequency and co-occurrence, topic modeling might help to identify common themes and establish connections across texts. The innovative suggestion of implementing more advanced techniques such as knowledge tensor-based analysis, as referenced in works such as Xi et al. [ 141 ] and Xi et al. [ 140 ], can be explored in future studies to identify important topics and differentiate between thematic areas in TikTok research. This approach may address potential biases in theme identification, providing improved clustering output and a more nuanced analysis. Moreover, by comparing TikTok’s academic research landscape with other social media platforms or related fields, knowledge tensor embedding can reveal unique characteristics, trends, or patterns specific to TikTok. Finally, the bibliometric and topic modeling analysis of specific journals publishing TikTok research is encouraged. A more diversified approach in terms of methods, data sources, and journal selection can also contribute to a more balanced view and a better understanding of the landscape of TikTok research, thereby minimizing the potential biases present in this study.

Data availability

The full list of references used for this review is available from the authors upon request.

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Rejeb, A., Rejeb, K., Appolloni, A. et al. Foundations and knowledge clusters in TikTok (Douyin) research: evidence from bibliometric and topic modelling analyses. Multimed Tools Appl 83 , 32213–32243 (2024). https://doi.org/10.1007/s11042-023-16768-x

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How U.S. Adults Use TikTok

Around half of adult tiktok users in the u.s. have never posted a video themselves. and a minority of users produce the vast majority of content, table of contents.

• Who posts videos to TikTok
• How posters differ from non-posters in their use of TikTok
• What TikTok users think of their ‘For You’ page
• Acknowledgments
• The American Trends Panel survey methodology
• Analysis of TikTok behavioral data
• Measuring TikTok adoption

Pew Research Center conducted this study to gain insight into TikTok users’ views of and behaviors on the site, as well as how those opinions might vary based on their posting activity. To conduct this analysis, we surveyed 2,745 U.S. adult TikTok users in August 2023. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP) – an online survey panel that is recruited through national, random sampling of residential addresses – and indicated that they use TikTok.

869 of these respondents volunteered a valid TikTok handle (their unique username preceded by an “@” sign) for research purposes. This allowed us to analyze their actual (observed) behaviors on the platform and compare them with their responses to the survey.

Here are the questions used for the report , along with responses, and its methodology .

A new Pew Research Center study matching the survey responses and on-site behaviors of U.S. adult TikTok users finds that a minority of avid posters create the vast majority of content on the site. And most users post seldom, if at all – instead using TikTok primarily to view and consume content made by others.

These findings come at a time when one-third of U.S. adults say they use the site and a growing share get news there . Among our key findings about how the American public is using TikTok:

A small share of users are responsible for producing the majority of TikTok content. The top 25% of U.S. adults on TikTok by posting volume produce 98% of all publicly accessible videos from this group. This is in line with the Center’s previous research on Twitter users , which found a similar ratio of highly active users creating the majority of content on the platform.

The typical TikTok user posts seldom, if ever. About half of all U.S. adults on the site have never posted a video themselves. And the typical user has not added any information to the “bio” field on their account.

The posting behaviors of younger adults do not stand out dramatically from other age groups. Users ages 18 to 34 are much more likely than their older counterparts to use TikTok in the first place. But around half of these younger users have ever posted on the site – similar to the share among users ages 35 to 49.

Users who have posted videos on TikTok are more active on the platform in general than non-posters. Posters typically follow more users, have more followers themselves, are more likely to have filled out their account bio and are somewhat more likely to find the content of their “For You” page extremely interesting.

TikTok users are more likely than not to find their “For You” page interesting. TikTok is defined by its algorithmically curated “For You” page, and users generally like the content the algorithm serves them. Some 40% of users say this content is either extremely or very interesting to them, far more than the 14% in total who say it is not too or not at all interesting.

The study began with a survey conducted in August 2023 of 2,745 U.S. adult TikTok users. It includes direct observation of the accounts and posting behavior of 869 respondents who volunteered to share their account handle for research purposes.

All these accounts – regardless of their privacy settings – contained basic account metadata. This includes their bio and display name fields, counts of followers and followed accounts, and the total number of “likes” the user had received on any videos they posted. For accounts set to public, we were also able to observe any public videos posted to the account to get a better understanding of adult TikTok users’ posting behavior.

• Americans’ social media use in 2023
• More Americans are getting news on TikTok
• What the public thinks about banning TikTok

Around half (52%) of U.S. adults on TikTok have ever posted a video on the platform. 1 And although there are substantial differences in which groups of Americans use TikTok in the first place, there are only modest differences in the posting behavior of users based on their demographic characteristics. Notably, there are no significant differences in the share of users who have posted on the site based on gender, political affiliation or educational attainment.

TikTok use is especially prevalent among younger adults – 56% of all U.S. adults ages 18 to 34 say they use the platform. But 52% of users in this age group have posted a video to their account. That is identical to the average among users overall, and similar to the share of users ages 35 to 49 who have ever posted.

A minority of users produce the majority of TikTok content from U.S. adults

While about half of U.S. adult TikTok users have ever posted a video at all, an even smaller share – 40% – have posted videos that are publicly visible. As a result, a relatively small share of users produce the vast majority of content that appears on the platform. 2

The typical TikTok user does not customize their bio

TikTok users do not tend to present a detailed profile of themselves on their accounts.

Although 70% of users have changed their account nickname from the site-provided default, an identical share have not added any information to the “bio” field on their account. The median U.S. adult user follows 154 other accounts but has just 36 accounts who follow them – and has received no likes from other users.

TikTok users who post on the platform differ from non-posters in several important ways. Those who have ever posted a video are nearly five times as likely to have customized the bio field on their profile. They are also a bit more likely to have updated their account nickname from its default.

Posters also engage with a lot more other accounts on TikTok: A typical (median) poster follows nearly four times as many other accounts as someone who doesn’t post, and they have more followers as well. While it’s true that a small share of U.S. adults on TikTok are highly prolific, not everyone who posts videos does this a lot. The median poster has put up a total of six public videos in the life of their accounts and received a total of 149 likes in return.

Some 85% of TikTok users say the content on their “For You” page is at least somewhat interesting, including 40% who call it either extremely or very interesting. Only 14% say it is not too or not at all interesting.

Younger users are especially interested in the content they see on the platform. Some 47% of users ages 18 to 34 say they find the videos on their “For You” page either extremely or very interesting, compared with 36% of users ages 35 to 49 and 31% of those 50 or older.

There are only modest differences on this question based on other demographic factors like gender, political affiliation or educational attainment. Similar shares of posters and non-posters find the “For You” page at least very interesting.

But posters are slightly more likely to report the highest level of interest in the material that TikTok’s content algorithm suggests to them. Some 17% of these users say they find the content of their “For You” page extremely interesting, compared with 11% of non-posters.

• On TikTok, videos can be listed either publicly or privately, but total “like” counts for the whole account are public, even if associated videos are private. Therefore, we consider an account to have posted content if there are any public videos on the account, or if the account is set to private but there are likes recorded on the account. ↩
• Due to the privacy settings of some accounts, we could only count videos that were publicly listed on TikTok in this analysis. ↩

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How Americans Navigate Politics on TikTok, X, Facebook and Instagram

How americans get news on tiktok, x, facebook and instagram, 6 facts about americans and tiktok, whatsapp and facebook dominate the social media landscape in middle-income nations, americans’ social media use, most popular, report materials.

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What Makes TikTok so Addictive?: An Analysis of the Mechanisms Underlying the World’s Latest Social Media Craze

Author: Sophia Petrillo

The health impacts of social media addiction remain somewhat unknown. Recent studies indicate variable health effects depending on the severity of the addiction, and increased social media use predicts more significant health consequences. One study investigating the impact of social media addiction on stress among employees of 13 companies in Thailand found that those with a higher degree of addiction appear to have a lower capacity for mindfulness (i.e. the ability to be fully engaged with the present moment). Social media addiction may reduce productivity and success in work, education, and other areas of life. Additionally, the study revealed that individuals experiencing addiction to social media choose emotion-focused coping to alleviate stress rather than problem-focused coping. In contrast to problem-focused coping, in which an individual takes actions targeted at the source of the problem, emotion-focused coping involves efforts to reduce the emotional severity of a situation as a means of resolving the problem. However, the employment of social media to reduce stress qualifies as unhealthy use and may increase emotional exhaustion. Those who are addicted often rely on social media to distract from real-life problems, which masks them and prevents addressing underlying issues. 1

Generally, social media has been linked with several adverse health impacts, particularly in transitional-age youths and adolescents. For example, more frequent daily social media site visits have been associated with higher odds of depression among U.S. individuals between the ages of 19 and 32, and corresponding findings have been reported internationally. 2 Furthermore, two separate studies, one on Scottish adolescents and another on U.S. college students, both indicated a relationship between increased use of social media and heightened levels of anxiety. 3,4 Associations between social media use and poor sleep and unhealthy eating habits have also been supported by nationally- and internationally-based studies. 5,6 Taken together, these findings suggest that the implications of social media addiction can be damaging to both individual and population health.

One social media platform that has seen a significant increase in popularity recently is TikTok. Reminiscent of newly-retired platforms, Vine and Musical.ly, regarding the type and format of app content, TikTok features short-form videos on every topic imaginable. At first featuring lip-synching and dancing to popular songs, current content has expanded to now include comedy, technical skill instruction, fitness inspiration, and myriad other categories. In addition, users can create original content and respond to content made by others through likes, comments, and reshares. Another key component of the app is the “For You” page, a feed specifically curated for each user by the app based on user activity and interaction with other content. Certain individuals have taken advantage of the platform as a marketing tool, establishing themselves as “influencers;” many companies also utilize the app to promote their products and messages. The global audience is heavily skewed towards younger generations, with almost half of its users under age 34, and teenagers make up nearly one-third of accounts. Overall, the platform had over 800 million users in 2019 and is expected to exceed 1 billion users by the end of 2020. Its current economic valuation of $75 million qualifies it as the world’s most valuable startup. Since its popularity spike in 2018, TikTok has surpassed other traditional social media apps such as Instagram and Facebook as the most-downloaded social media app. 7 Clearly, TikTok is well-established, rivaling other platforms for supremacy in the social-media world. 

The ‘like’ button is a hallmark of nearly all social media platforms. The action of ‘liking’ social media content has recently become so popular that Merriam Webster now lists an alternative definition of ‘like’ in the dictionary as “to electronically register one’s approval of (something such as an online post or comment) for others to see (as by clicking on an icon designed for that purpose).” 8 The button was first created in 2005 on Vimeo as an alternative way for users to react to videos that felt less concrete than ‘favoriting’ them; its later introduction to Facebook in 2009 and subsequent alterations to its functionality contributed to its establishment as a fixture of social media platforms. 9 ‘Likes’ provide information on social norms and indicate the societal view of particular media that is posted, influencing how individuals perceive it. Additionally, ‘likes’ offer information to social media companies and other websites where there are ‘like’ button plugins so they can more specifically tailor their content to users to keep them more engaged without directly asking their preferences. 10 The ‘like’ button was instrumental in the rapid growth of Facebook in 2010 and has had similar effects on TikTok over the past few years. Thus, although the platforms differ in their content and audiences, they are remarkably alike at the structural level.

In alignment with traditional mechanisms of reward-based learning and facilitation of the habit and addiction loops, ‘likes’ serve as a reward for social media users. A study utilizing a functional MRI paradigm to mimic the “Instagram experience” of viewing “liked” photos demonstrated increased neural activity in regions traditionally associated with reward, namely the nucleus accumbens, and provided evidence for the influence of virtual peer endorsement through ‘likes’ as a form of quantifiable social endorsement among users; accordingly, receipt of a ‘like’ indicates that others approve of an individual’s content. 11 This satisfies the human desire for acceptance by others, particularly those they respect and whose opinions they value; these individuals often comprise one’s ‘friends’ or ‘followers’ on social media. Dopamine release is a key part of the positive feedback loop that drives reward-based learning; increased dopaminergic activity in the brain in response to receiving a ‘like’ encourages future social media use and continued content publication in hopes that the pleasurable experience will re-occur. 12 ‘Likes’ also keep users engaged with social media platforms by representing a form of investment; ‘liking’ content elicits the psychological experience of investment in the platform, and the more invested people are, the more likely they are to care about it and return to the website or app in the future. Evidently, ‘likes’ are gratifying in multiple ways — it feels good to receive likes from other people, and it also feels good to give ‘likes’ to other people in the same way that it feels good to give people gifts. For both forms, the presence of the like button allows instant gratification, which drives habitual use and addiction through positive reinforcement. 13

Undoubtedly, the appeal and entertainment value of content posted on TikTok is a major factor in its popularity. Users are intrigued by videos posted by others and may recreate these videos or publish original content. However, the platform’s success is also heavily influenced by elements of the app itself, and it has been argued that certain app features drive the formation and sustenance of addictions to the platform. Recent reports reveal that users spend an average of 46 minutes per day on the app and open it eight times daily; considering the maximum length of videos is 15 seconds, they may watch upwards of 180 videos per day on average. 14 Like other social media platforms, the infinite scroll and variable reward pattern of TikTok likely increase the addictive quality of the app as they may induce a flow-like state for users that is characterized by a high degree of focus and productivity at the task at hand, 15 whether that be a game, one’s social media feed, or another virtual activity. Once immersed in the flow-like state, users may experience a distorted sense of time in which they do not realize how much time has passed. Furthermore, the app interface itself is straightforward and user-friendly, with only a limited number of buttons and sections of the app for users to navigate, which further enables entrance into “flow.” 16 Videos are short, which is ideal given the decreasing attention capacity of youths in the 21st century. When they play, they consume the entire device screen, which creates an immersive experience for users. 17

The personalized “For You” stream created by artificial intelligence (AI) for each user has also been identified as a key contributor to TikTok addiction. TikTok differs from other social media apps because an individual’s feed is not based on deliberate choices made about the content they want to see. Instead, AI presents individuals with content and uses their reactions to it (in the form of likes, comments, and reshares) to determine other content they might like, facilitating a continuous cycle that starts from the first use and becomes increasingly accurate with repeated engagement. 18 All of the in-app features prolong the time that users spend on the app, which increases the addictive capacity of the platform. To further support this effort, developers constantly change the app layout and add new features so that users spend more time on the app navigating and adjusting to the new design.

Although the similarity may not be immediately evident, analysis of social media apps reveals that they are designed to function like slot machines — the “swipe down” feature required to refresh one’s feed mirrors pulling a slot machine lever, and the variable pattern of reward in the form of entertaining videos on TikTok simulates the intermittent reward pattern of winning or losing on a slot machine; this pattern keeps individuals engaged under the impression that the next play might be “the one.” 19 The striking parallelism between social media apps and slot machines is intriguing given that gambling is the only behavioral addiction currently recognized by the DSM-5. Provided that social media apps are functionally akin to slot machines, it is likely that the use of these apps is just as addictive as slot machines and fosters social media addiction, much like how slot machines contribute to gambling addiction.

Taken together, specific consideration of TikTok in the larger context of social media platforms reveals that “TikTok addiction” is likely a result of a combination of effects. Like other substance and behavioral addictions, it is expected that there are dispositional factors involved in the development of addiction to TikTok. This is because certain lived experiences and personality traits are believed to predict a tendency for engagement in habitual behaviors and addiction. Although these characteristics are often unpreventable, therapeutic and medicative treatments may effectively reduce their influence on an individual’s behavior, so this driver of TikTok addiction may not be too significant.

Unfortunately, it appears that structural and contextual aspects of TikTok are greater contributors to addiction than dispositional attributes of users. Elements of app design and functionality, namely the variable reward pattern of the content stream, the simple, “flow-inducing” interface, and the capability for “endless scroll,” capitalize on classical conditioning and reward-based learning processes to facilitate the formation of habit loops and encourage addictive use. Unlike dispositional drivers of “TikTok addiction,” situational elements of the platform are engineered by app developers, and thus, could be eliminated. However, developers are unwilling to relent with the knowledge that their app’s success depends on its ability to manipulate users to continue use despite any adverse consequences. Although this behavior is conscious and deliberate, whereas dispositional factors are often unconscious and uncontrollable, changing the attitudes and behavior of those in the social media industry may pose a greater challenge to public health efforts to reduce “TikTok addiction” than simply treating misaligned personality traits; this is the reality of living in an increasingly digital and technologically-based world.

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Court documents offer a window into how this happens

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I N APRIL HILARY CASS , a British paediatrician, published her review of gender-identity services for children and young people, commissioned by NHS England. It cast doubt on the evidence base for youth gender medicine. This prompted the World Professional Association for Transgender Health ( WPATH ), the leading professional organisation for the doctors and practitioners who provide services to trans people, to release a blistering rejoinder. WPATH said that its own guidelines were sturdier, in part because they were “based on far more systematic reviews”.

Systematic reviews should evaluate the evidence for a given medical question in a careful, rigorous manner. Such efforts are particularly important at the moment, given the feverish state of the American debate on youth gender medicine, which is soon to culminate in a Supreme Court case challenging a ban in Tennessee. The case turns, in part, on questions of evidence and expert authority.

Court documents recently released as part of the discovery process in a case involving youth gender medicine in Alabama reveal that WPATH ’s claim was built on shaky foundations. The documents show that the organisation’s leaders interfered with the production of systematic reviews that it had commissioned from the Johns Hopkins University Evidence-Based Practice Centre ( EPC ) in 2018.

From early on in the contract negotiations, WPATH expressed a desire to control the results of the Hopkins team’s work. In December 2017, for example, Donna Kelly, an executive director at WPATH , told Karen Robinson, the EPC ’s director, that the WPATH board felt the EPC researchers “cannot publish their findings independently”. A couple of weeks later, Ms Kelly emphasised that, “the [ WPATH ] board wants it to be clear that the data cannot be used without WPATH approval”.

Ms Robinson saw this as an attempt to exert undue influence over what was supposed to be an independent process. John Ioannidis of Stanford University, who co-authored guidelines for systematic reviews, says that if sponsors interfere or are allowed to veto results, this can lead to either biased summaries or suppression of unfavourable evidence. Ms Robinson sought to avoid such an outcome. “In general, my understanding is that the university will not sign off on a contract that allows a sponsor to stop an academic publication,” she wrote to Ms Kelly.

Months later, with the issue still apparently unresolved, Ms Robinson adopted a sterner tone. She noted in an email in March 2018 that, “Hopkins as an academic institution, and I as a faculty member therein, will not sign something that limits academic freedom in this manner,” nor “language that goes against current standards in systematic reviews and in guideline development”.

Not to reason XY

Eventually WPATH relented, and in May 2018 Ms Robinson signed a contract granting WPATH power to review and offer feedback on her team’s work, but not to meddle in any substantive way. After wpath leaders saw two manuscripts submitted for review in July 2020, however, the parties’ disagreements flared up again. In August the WPATH executive committee wrote to Ms Robinson that WPATH had “many concerns” about these papers, and that it was implementing a new policy in which WPATH would have authority to influence the EPC team’s output—including the power to nip papers in the bud on the basis of their conclusions.

Ms Robinson protested that the new policy did not reflect the contract she had signed and violated basic principles of unfettered scientific inquiry she had emphasised repeatedly in her dealings with WPATH . The Hopkins team published only one paper after WPATH implemented its new policy: a 2021 meta-analysis on the effects of hormone therapy on transgender people. Among the recently released court documents is a WPATH checklist confirming that an individual from WPATH was involved “in the design, drafting of the article and final approval of [that] article”. (The article itself explicitly claims the opposite.) Now, more than six years after signing the agreement, the EPC team does not appear to have published anything else, despite having provided WPATH with the material for six systematic reviews, according to the documents.

No one at WPATH or Johns Hopkins has responded to multiple inquiries, so there are still gaps in this timeline. But an email in October 2020 from WPATH figures, including its incoming president at the time, Walter Bouman, to the working group on guidelines, made clear what sort of science WPATH did (and did not) want published. Research must be “thoroughly scrutinised and reviewed to ensure that publication does not negatively affect the provision of transgender health care in the broadest sense,” it stated. Mr Bouman and one other coauthor of that email have been named to a World Health Organisation advisory board tasked with developing best practices for transgender medicine.

Another document recently unsealed shows that Rachel Levine, a transwoman who is assistant secretary for health, succeeded in pressing wpath to remove minimum ages for the treatment of children from its 2022 standards of care. Dr Levine’s office has not commented. Questions remain unanswered, but none of this helps WPATH ’s claim to be an organisation that bases its recommendations on science. ■

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This article appeared in the United States section of the print edition under the headline “Marking their own homework”

United States June 29th 2024

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Google Search Ranks AI Spam Above Original Reporting in News Results

Recently, I was using Google and stumbled upon an article that felt eerily familiar.

While searching for the latest information on Adobe’s artificial intelligence policies, I typed “adobe train ai content” into Google and switched over to the News tab. I had already seen WIRED’s coverage that appeared on the results page in the second position: “Adobe Says It Won’t Train AI Using Artists’ Work. Creatives Aren’t Convinced.” And although I didn’t recognize the name of the publication whose story sat at the very top of the results, Syrus #Blog, the headline on the article hit me with a wave of déjà vu: “When Adobe promised not to train AI on artists’ content, the creative community reacted with skepticism.”

Clicking on the top hyperlink, I found myself on a spammy website brimming with plagiarized articles that were repackaged, many of them using AI-generated illustrations at the top. In this spam article, the entire WIRED piece was copied with only slight changes to the phrasing. Even the original quotes were lifted. A single, lonely hyperlink at the bottom of the webpage, leading back to our version of the story, served as the only form of attribution.

A list of news articles within Google's search results show an AI spam version of a WIRED story listed at the top, with the original reported story listed second.

The bot wasn’t just copying journalism in English—I found versions of this plagiarized content in 10 other languages, including many of the languages that WIRED produces content in, like Japanese and Spanish .

Articles that were originally published in outlets like Reuters and TechCrunch were also plagiarized on this blog in multiple languages and given similar AI images. During late June and early July, while I was researching this story, the website Syrus appeared to have gamed the News results for Google well enough to show up on the first page for multiple tech-related queries.

For example, I searched “competing visions google openai” and saw a TechCrunch piece at the top of Google News. Below it were articles from The Atlantic and Bloomberg comparing the rival companies’ approaches to AI development. But then, the fourth article to appear for that search, nestled right below these more reputable websites, was another Syrus #Blog piece that heavily copied the TechCrunch article in the first position.

As reported by 404 Media in January , AI-powered articles appeared multiple times for basic queries at the beginning of the year in Google News results. Two months later, Google announced significant changes to its algorithm and new spam policies, as an attempt to improve the search results. And by the end of April, Google shared that the major adjustments to remove unhelpful results from its search engine ranking system were finished. “As of April 19, we’ve completed the rollout of these changes. You’ll now see 45 percent less low-quality, unoriginal content in search results versus the 40 percent improvement we expected across this work,” wrote Elizabeth Tucker, a director of product management at Google, in a blog post .

Despite the changes, spammy content created with the help of AI remains an ongoing, prevalent issue for Google News.

“This is a really rampant problem on Google right now, and it's hard to answer specifically why it's happening,” says Lily Ray, senior director of search engine optimization at the marketing agency Amsive . “We've had some clients say, ‘Hey, they took our article and rehashed it with AI. It looks exactly like what we wrote in our original content but just kind of like a mumbo-jumbo, AI-rewritten version of it.’”

At first glance, it was clear to me that some of the images for Syrus’ blogs were AI generated based on the illustrations’ droopy eyes and other deformed physical features—telltale signs of AI trying to represent the human body.

Now, was the text of our article rewritten using AI? I reached out to the person behind the blog to learn more about how they made it and received confirmation via email that an Italian marketing agency created the blog. They claim to have used an AI tool as part of the writing process. “Regarding your concerns about plagiarism, we can assure you that our content creation process involves AI tools that analyze and synthesize information from various sources while always respecting intellectual property,” writes someone using the name Daniele Syrus over email.

They point to the single hyperlink at the bottom of the lifted article as sufficient attribution. While better than nothing, a link which doesn’t even mention the publication by name is not an adequate defense against plagiarism . The person also claims that the website’s goal is not to receive clicks from Google’s search engine but to test out AI algorithms in multiple languages .

When approached over email for a response, Google declined to comment about Syrus. “We don’t comment on specific websites, but our updated spam policies prohibit creating low-value, unoriginal content at scale for the purposes of ranking well on Google,” says Meghann Farnsworth, a spokesperson for Google. “We take action on sites globally that don’t follow our policies.” (Farnsworth is a former WIRED employee.)

Looking through Google’s spam policies, it appears that this blog does directly violate the company’s rules about online scraping. “Examples of abusive scraping include: … sites that copy content from other sites, modify it only slightly (for example, by substituting synonyms or using automated techniques), and republish it.” Farnsworth declined to confirm whether this blog was in violation of Google’s policies or if the company would de-rank it in Google News results based on this reporting.

What can the people who write original articles do to properly protect their work ? It’s unclear. Though, after all of the conversations I’ve had with SEO experts, one major through line sticks out to me, and it’s an overarching sense of anxiety.

“Our industry suffers from some form of trauma, and I'm not even really joking about that,” says Andrew Boyd, a consultant at an online link-building service called Forte Analytica . “I think one of the main reasons for that is because there's no recourse if you're one of these publishers that's been affected. All of a sudden you wake up in the morning, and 50 percent of your traffic is gone.” According to Boyd, some websites lost a majority of their visitors during Google’s search algorithm updates over the years.

While many SEO experts are upset with the lack of transparency about Google’s biggest changes, not everyone I spoke with was critical of the prevalence of spam in search results. “Actually, Google doesn't get enough credit for this, but Google's biggest challenge is spam.” says Eli Schwartz, the author of the book Product-Led SEO . “So, despite all the complaints we have about Google’s quality now, you don’t do a search for hardware and then find adult sites. They’re doing a good enough job.” The company continues to release smaller search updates to fight against spam.

Yes, Google sometimes offers users a decent experience by protecting them from seeing sketchy pornography websites when searching unrelated, popular queries. But it remains reasonable to expect one of the most powerful companies in the world—that has considerable influence over how online content is created, distributed, and consumed—to do a better job of filtering out plagiarizing, unhelpful content from the News results.

“It's frustrating, because we see we're trying to do the right thing, and then we see so many examples of this low-quality, AI stuff outperforming us,” says Ray. “So I'm hopeful that it's temporary, but it's leading to a lot of tension and a lot of animosity in our industry, in ways that I've personally never seen before in 15 years.” Unless spammy sites with AI content are stricken from the search results, publishers will now have less incentive to produce high-quality content and, in turn, users will have less reason to trust the websites appearing at the top of Google News.

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Best AI Chatbots of 2024

ChatGPT isn't the only free AI chatbot on the net. We tested and compared them to figure out the best one for you.

The launch of AI chatbot ChatGPT in late 2022 completely transformed how we interact with technology. Generative AI can answer questions in WhatsApp chats , summarize emails in Outlook , create "genmojis" in iMessage and spit out answers to complex questions with ease. 

Now pretty much every major tech company has launched its own chatbot to compete with ChatGPT, including Google Gemini , Microsoft Copilot and Meta AI . Smaller startups also have working AI chatbots that compete well against trillion-dollar companies, including Anthropic's Claude and Perplexity.

At CNET, we reviewed all of those AI chatbots to find the best one for you (side note: doing so rewired my brain ). The list below focuses on free versions as opposed to paid ones, but note that most AI chatbots do have a paid tier that often performs better than the free version. For most people, however, the free chatbot will get you 90% of what you need. 

What is the best AI chatbot of 2024 so far?

Claude by Anthropic is the best AI chatbot overall right now. That doesn't mean ChatGPT or Perplexity are bad. Actually, both have their own advantages and disadvantages. Overall, though, the breadth at which Claude is able to answer questions and its calibration towards nuance and engagement should make it the most valuable to most people.

Best overall AI chatbot

Anthropic Claude

• Gives nuanced answers with detail
• Fast and well organized

Don't like

• Not connected to the internet
• Doesn't automatically provide sources

Claude by Anthropic is CNET Editors' Choice for the best overall AI chatbot . That doesn't mean it excels at every task compared to the competition. Rather, it does a consistent job and goes further than what's coming out of Google, Microsoft, Perplexity and OpenAI at the free tier. 

The major things holding Claude back are its apathetic linking to outside sources and the lack of an Android app. If Anthropic could better tune Claude to have access to the open internet to link to sources and shopping links, it'd make the chatbot a true one-stop-shop. Despite the omission, the quality of its responses and its willingness to engage in heady conversations make it the most useful overall. I also like how Claude is more willing to engage and ask the user questions.

Read our Claude review .

Second-best AI chatbot

ChatGPT Free

• Gives meaningful answers with a good amount of context
• Does most things well, including research, email writing and recommendations
• Could tap more into historical context for explanations
• Can be slow at times
• Asking for sources can be tedious

A close contender for the top spot is OpenAI's ChatGPT-4o, which is now available for free , albeit with caveats. OpenAI says that while free users will have access to its ChatGPT-4o model, when usage limits are reached based on demand, then free users will revert back to the older 3.5 model. While free users are able to ask ChatGPT-4o up to 40 messages every three hours , that number might be reduced due to high demand. 

ChatGPT Free offers detailed and nuanced answers, but they weren't quite as high-quality as Claude. Putting the two side-by-side, I noticed slight differences in the quality of answers. I particularly liked the specificity that Claude delved into when asking heavier political questions, such as the morality of the Israel-Palestine conflict. And like Claude, ChatGPT doesn't link to outside sources. Sometimes when you ask it to provide sources, it'll suggest things to Google or YouTube.

CNET doesn't have a full review of ChatGPT Free yet (that's coming soon), but I've tested it extensively enough to give it the second-place spot on this list.

Read our ChatGPT 4 review .

Best AI chatbot for research

• Includes list of all sources used
• Gives nuanced answers in an easy-to-follow list
• Too much reliance on Reddit posts and forums, which aren't citable for most people

Perplexity did the best job for research in my testing. The team at Perplexity has tuned its AI chatbot to add loads of links into answers. Hyperlinks can include journalistic publications, Reddit posts and even YouTube videos. 

When writing essays or articles, links to actual sources are critical. Perplexity actually lists each source in a handy sidebar that can be easily accessed. And, thankfully, the sources aren't simply Wikipedia, which won't fly with your college professor. The only downside is that Perplexity does rely on forum posts and Reddit for its answers, which aren't journalistic or scholarly. I'm sure the information is handy, but that will mean doing more research on your part to ensure those factoids are accurate and can be sourced to something more attributable.

Read our Perplexity review .

Best AI chatbot for shopping

Google Gemini

• Gives solid shopping recommendations and product research
• Links to Amazon products directly
• Connected to open internet with option to double-check against Google Search
• Can make stuff up
• Doesn't answer questions on difficult subject matters

Google's AI engine has been prone to hallucinations -- simply making up stuff -- such as when Google's AI overviews feature was rolled back last month when it suggested people eat rocks . When I reviewed Gemini earlier this year, it was the lowest-rated AI chatbot out of the bunch, with a dismal 5/10 score. 

But AI chatbots aren't stationary pieces of technology that exist in a vacuum. Gemini has improved since I reviewed it back in April, although it still hallucinates. In my recent testing, for example, Gemini made up the name of a college professor and the name of an Adult Swim executive. And it simply refuses to answer heavier political questions, as does Microsoft's Copilot. 

But the one area in which Gemini did excel was in how-to guides and shopping recommendations. When I asked how to cut a perfect circle in a piece of vinyl, not only did Gemini give a list of instructions, it also linked to products on Amazon that could make the process easier. None of the other chatbots linked to Amazon products. When it came to shopping recommendations, Gemini gave quick and concise answers with links to where to buy products.

Read our Google Gemini review .

How we tested AI chatbots

Testing for AI requires constant tweaking. Because companies are always looking at ways to improve their AI models, tests that worked to push AI chatbots last year or even last month might not work today. That said, we try to test AI chatbots with questions we believe normal people will ask. We aren't necessarily trying to "break" AI chatbots with obtuse-sounding questions meant to confuse. Instead, we consider what might be asked when it comes to video game guides or shopping recommendations. Our tests also ask some heavier questions about difficult events happening around the world to see which are comfortable in actually engaging. 

The AI chatbots that sit on this list, generally, are able to take on the tougher questions and give believable answers with nuance. Like reading an article written by a university professor, we want AI chatbots to have that same level of consideration for historical context and competing interests to try and leave the reader with a better understanding from a higher-level perspective. 

For more, check out How We Test AI .

Factors to consider

When using an AI chatbot, keep your privacy and sensitive information in mind. For example, it might seem benign to have an AI chatbot summarize your company's meeting notes . But, that data could inadvertently be used to train AI models further, and you've essentially lost control of it, according to experts. Plus, it's totally within the realm of the privacy policies for AI companies to sell that data to third parties. While Google's privacy policy might state that it'll remove any personally identifiable information, it's still best to err on the side of caution. Google actually outright recommends you don't upload any confidential information whatsoever . 

Other AI chatbots we tested

Microsoft Copilot: This chatbot, found on the Bing search engine, uses GPT-4 Turbo, a version of OpenAI's GPT-4 that is optimized for speed. While Copilot is still a serviceable chatbot, it doesn't answer questions with the same level of detail and nuance as Claude, ChatGPT-4o and Perplexity. Plus, its outright refusal to answer questions that are politically sensitive in nature is a demerit.

Meta AI: Unlike other AI chatbots, Meta AI not only has its own dedicated webpage , but is integrated into Instagram, WhatsApp, Facebook and the Ray-Ban Meta smart glasses . When CNET's Katelyn Chedraoui reviewed Meta AI earlier this year, she found it to be decent overall, but noncompetitive with the competition. While Meta AI did provide good shopping advice with some cajoling, and excelled in recipes, it fell short in other areas. When it came to research, despite it being connected to Google and Bing, it sourced nonscholarly papers, like an elementary school lesson plan. 

ChatGPT 3.5 : This service, which I tested earlier in 2024, has since been replaced by what OpenAI calls ChatGPT Free (which utilizes a combination of GPT-4o, GPT-4 and GPT-3.5). It is a competent AI chat engine that answers difficult questions with easy-to-understand language. It doesn't hallucinate at the rate of Google Gemini, but there really isn't a reason to switch ChatGPT to 3.5 when you can use 4o and 4 for free. 

AI chatbot FAQs

Do i need to use ai.

AI is a handy tool and can be a timesaver, but it isn't necessary in day-to-day life. It's totally possible to still Google Search your queries and read through articles to get the answer you're looking for. Heck, it probably gives your brain more of a mental workout!

What is the best free AI?

Anthropic Claude is currently CNET's choice for the best free AI chatbot. Free versions of ChatGPT and Perplexity also offer great results with specific advantages and disadvantages. Google's Gemini is great for shopping recommendations. Like Gemini, Microsoft's CoPilot won't answer heavier and more controversial questions.

What is the best AI on mobile?

While there are mobile apps for Gemini, Copilot and Perplexity, we prefer the ChatGPT app the most. It has a clean interface and is easy to navigate. But really, any app will get the job done. Unfortunately, Claude only has a mobile app for iOS and not Android. 

Can AI be trusted?

Geoffrey Hinton, the researcher who developed the concept of neural networks and who is considered the godfather of AI, feels less enthusiastic about the technology he helped birth . As for using AI chatbots on a day-to-day basis, they're handy tools that can synthesize the world's information for you in seconds, saving you lots of research time. Just be aware that sometimes AI chatbots get things wrong and it's good to do a Google search for things that sound a bit dubious. Also, be careful when giving AI chatbots sensitive information. Don't ask an AI chatbot to summarize your company's trade secrets, as privacy policies give AI companies wide latitude to do with that data as they please.

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Deconstructing TikTok Videos on Mental Health: Cross-sectional, Descriptive Content Analysis

Corey h basch.

1 Department of Public Health, William Paterson University, Wayne, NJ, United States

Lorie Donelle

2 Arthur Labatt Family School of Nursing, Western University, London, ON, Canada

Joseph Fera

3 Department of Mathematics, Lehman College, City University of New York, Bronx, NY, United States

Christie Jaime

Associated data.

Negative mental health sentiments portrayed in the comments associated with 100 TikTok videos.

Sentiments of social support and collective optimism portrayed in the comments associated with 100 TikTok videos.

Social media platforms that are based on the creation of visual media, such as TikTok, are increasingly popular with adolescents. Online social media networks provide valuable opportunities to connect with each other to share experiences and strategies for health and wellness.

The aim of this study was to describe the content of the hashtag #mentalhealth on TikTok.

This cross-sectional, descriptive content analysis study included 100 videos with the hashtag #mentalhealth on TikTok. All videos that included the hashtag #mentalhealth were analyzed and coded for the presence of content categories. Additionally, the comments to each video were viewed and coded for content in the following themes: offering support or validation; mentioning experience with suicide or suicidal ideation; mentioning experience with self-harm; describing an experience with hospitalization for mental health issues; describing other mental health issues; and sharing coping strategies, experiences of healing, or ways to feel better.

Collectively, the 100 videos studied received 1,354,100,000 views; 266,900,000 likes; and 2,515,954 comments. On average, each video received 13,406,930.69 (SD 8,728,095.52) views; 2,657,425.74 (SD 1,449,920.45) likes; and 24,910.44 (SD 21,035.06) comments. The only content category observed in most (51/100, 51%) of the videos included in the sample was “general mental health.” The remaining content categories appeared in less than 50% of the sample. In total, 32% (32/100) of the videos sampled received more than the overall average number of likes (ie, more that 2.67 million likes). Among these 32 videos, 23 (72%) included comments offering support or validation and 20 (62%) included comments that described other mental health issues or struggles.

Conclusions

With over 1 billion cumulative views, almost half of the assessed TikTok videos included in this study reported or expressed symptoms of mental distress. Future research should focus on the potential role of intervention by health care professionals on social media.

Introduction

Access to accurate and accessible health information, support, and services are required for effective health care decision-making. This applies across the health care continuum and is inclusive of self-health promotion and participation in shared decision-making with health care provider teams [ 1 - 6 ]. Individuals rely on family, friends, and health care professionals for support, yet seek health-related information online at the same time [ 7 , 8 ]. In general, adolescents live in a hybrid reality—a mix of offline and online worlds [ 9 ]. They are increasingly seeking information about healthy lifestyles (fitness, diet), gender identity, sexual health, and mental health issues from online websites, social media platforms, wearable self-tracking apps, and other adolescents within online communities [ 10 , 11 ]. However, adolescents are less accepting of online or wearable apps that require them to input information [ 7 ]. Overall, online media and social media apps are seen as simple to use, unidentifiable, and impartial sources of health information by adolescents [ 7 , 12 ]. Health-related stories from peers are particularly valued among adolescents [ 7 , 13 ]. Influencers on social media, adolescents who create content, and microcelebrities are increasingly important resources for health-related information and social support [ 7 , 14 - 16 ]. However, adolescents may find the sheer volume of online information challenging and are not always confident in their ability to discern accurate information from misinformation or disinformation [ 7 ].

Social media platforms that are based on the creation of visual media, such as TikTok, are popular with adolescents. TikTok, a video-based social media platform, has been leveraged as a way to disseminate health-related information, and this has been especially visible during the COVID-19 pandemic [ 17 ]. The vast reach of TikTok worldwide offers a unique approach for disseminating information to the millions of users ranging from children to adults. As a social media platform, TikTok creators combine music and dance attached to personal messages that are widely disseminated [ 17 ].

Several studies have been conducted on the health-related content on TikTok. These studies indicate that a wide range of issues have been examined, including health promoting and compromising issues. Examples include, but are not limited to, studies related to COVID-19 mitigation, eating disorders, vaping, climate change, and equity issues [ 12 , 18 - 26 ].

Specific to mental health information and social support, researchers determined that youth and young adults appreciated shared experiences within online discussion forums, citing accessibility, anonymity, inclusivity, sense of control, and mitigation of stigma as valued resource characteristics [ 12 ]. Preference for seeking health information online or through peer-to-peer sharing can reflect individuals’ concerns or experiences with nonaffirming or discriminatory health care providers [ 12 ]. Furthermore, peer-to-peer health information sharing may fill the gaps in social support from health systems, health-specific information, and insight into “how to live” with chronic diseases including mental health. In particular, select TikTok videos may serve as relevant educational resources for health care professionals’ education and training [ 12 ]. However, research exploring mental health content on TikTok is essentially absent from published research literature.

Online social media networks provide valuable opportunities to connect with each other to share experiences and strategies for health and wellness, such as meditation, mindfulness, stress relief, and those specific to mental health conditions [ 13 ]. Mental health issues are highly prevalent in adolescents. According to the World Health Organization, “globally, one in seven 10-19-year-olds experiences a mental disorder, accounting for 13% of the global burden of disease in this age group” [ 27 ]. Given these statistics, combined with the popularity of TikTok use in this age group [ 28 ], the aim of this study was to describe the content of the hashtag #mentalhealth on TikTok.

Data Collection and Analysis

This cross-sectional, descriptive content analysis study included videos with the hashtag #mentalhealth on TikTok. The methods were based on prior research and established methodology [ 24 , 29 , 30 ]. By using the “discover” function on the TikTok platform and a hashtag search of #mentalhealth, a sample of the first 100 videos was collected. At the time of the study, the hashtag had 25.3 billion views. This was the most viewed hashtag in this area at the time of the study (January 2022). Only English-language videos were considered for this sample. For each video, the date of posting and the number of views, comments, and likes were documented. All videos that included the hashtag #mentalhealth were analyzed and coded for the presence of additional content categories. The content categories included general mental health (nonspecific disorder), anxiety or fear, depression, stress, suicide, self-harm, interpersonal relationships, physical health conditions or variables, child or adolescent mental health, mental health stigma, statistics and the prevalence of mental health disorders or issues, biological and neurological influences of mental health, missing other people or connections due to COVID-19, personal experience, and coping techniques or treatment.

Additionally, the comments associated with each video were viewed and coded inductively for content in the following themes: offering support or validation; mentioning experience with suicide or suicidal ideation; mentioning experience with self-harm; describing an experience with hospitalization for mental health issues; describing other mental health issues or struggles; and sharing coping strategies, experiences of healing, or ways to feel better. All data were collected, categorized, and organized by a single reviewer (CJ), and a random number generator was used to identify a subset of (10%) the videos to be analyzed by a second reviewer (CB) to determine interrater reliability. The interrater reliability score (κ=0.97) indicated a high level of consensus. Microsoft Excel was used to record, organize, and analyze the data collected.

Ethical Considerations

This study was excluded from institutional ethics board review, as the William Paterson University Institutional Review Board does not review studies that do not involve human participants.

Overall, the 100 videos studied received 1,354,100,000 views; 266,900,000 likes; and 2,515,954 comments. On average, each video received 13,406,930.69 (SD 8,728,095.52) views; 2,657,425.74 (SD 1,449,920.45) likes; and 24,910.44 (SD 21,035.06) comments. Of the 100 videos, a majority (n=84, 84%) were classified as consumer-generated; only 13 (13%) were classified as influencer- or verified-user–generated, with the remaining classified as heath care professional–generated (n=1, 1%), television- or internet-based news (n=1, 1%), and television-based entertainment (n=1, 1%).

In Table 1 , the first column lists the 14 different content categories of the video data and the second column details how many of the 100 videos sampled included this content. The table also includes the number of views, likes, and comments that the videos with these particular features garnered. Relative percentages from the total are included as well. The content category “statistics and prevalence of mental health disorders or issues” was omitted from the table since it was not featured in any of the sampled videos.

Observed content, views, likes, and comments of 100 TikTok videos on mental health.

The only content category observed in a majority (51/100, 51%) of the videos sampled was “general mental health.” The remaining content categories appeared in less than 50% of the sample. “Personal experience” was the next most prevalent category observed in the videos and it appeared in 40% (40/100) of the sample. The remaining content categories appeared in less than 20% of the sample, with the following 5 content categories appearing in less than 5% of the sample: anxiety or fear, physical health conditions or variables, stress, mental health stigma, and missing other people or connections due to COVID-19.

Table 2 provides information about the themes noted in the videos’ comments. This table shows 6 different themes, the number of videos with comments that reflected these themes, and the associated number of views, likes, and comments of these videos. The most common themes observed in the videos’ comments sections were “offering support or validation” (61/100, 61%) and “describing other mental health issues or struggles” (49/100, 49%).

Themes noted in the videos’ comments and the associated number of views, likes, and comments.

In total, 32% (32/100) of the videos sampled received more than the overall average number of likes (ie, more than 2.67 million likes). Among these 32 videos, 23 (72%) included comments offering support or validation and 20 (62%) included comments describing other mental health issues or struggles. The remaining themes were included in ≥10 videos: shared coping strategies, experiences of healing, or ways to feel better (10/32, 31%); describing an experience with hospitalization for mental health issues (7/32, 22%); mentioning experiences with suicide or suicide ideation (6/32, 19%); and mentioning experience with self-harm (2/32, 6%).

The frequently used words excerpted from the comments section of the TikTok platform are shown in Multimedia Appendices 1 - 2 . Multimedia Appendix 1 shows the negative sentiments portrayed in the comments that reflect serious mental health concerns, which were expressed in response to participant-posted TikTok videos depicting issues of depression, grief, sadness, anger, loneliness, and trauma. In contrast, Multimedia Appendix 2 shows social support and collective optimism in the comments about the posted TikTok videos. These comments were caring and reflected encouragement, praise, and acceptance. It is important to note that these comments were generally presented in the context of support from those who allegedly have shared experiences or trauma.

Principal Findings

It is important to note the reach of the videos included in this study. With over 1 billion cumulative views, almost half of the assessed TikTok videos included in this study reported or expressed symptoms of mental distress. Other studies have observed the expression of mental ill-health within online social media platforms [ 31 ] and expressed concern about potentially traumatic and “triggering” TikTok videos as being detrimental to some viewers [ 32 ]. This is especially concerning given the frequency of screen time among adolescents. Many adolescents are predominant TikTok participants, and there is a potential for contribution to poor mental health outcomes from repetitious and prolonged viewing, especially if traumatic events are featured in the videos [ 32 ]. Recently, TikTok has acknowledged the substantial impact of their platform on users’ mental health and have provided additional resources in support of user safety, health, and mental wellness [ 33 ]. Specific to the issues of mental health, TikTok has produced well-being guides in partnership with the several international mental health organizations to support and uptake optimal messaging on the TikTok platform [ 34 ]. However, there is limited insight into the impact of traumatic or “triggering” events posted within the online platform [ 35 ], the use and impact of the TikTok mental health resources, or conversely, the health enhancing impact of positive and supportive messaging among youth who engage with social media [ 36 , 37 ]

Over 60% of the videos in this study had associated comments that were supportive and validating; this can signify the importance of the TikTok platform and the hashtag #mentalhealth as a possible “just-in-time” source of social support and personal validation that is made available without the need for planning, scheduling, and financial renumeration. Notably, comments that depict coping strategies were not overly common; they were apparent in about 10% of the videos with high numbers of collective views. Given the seriousness of the topics, these findings point to the fact that videos alone only tell part of the story. Health care professionals are active on social media and, specifically, TikTok [ 17 , 38 ]. Comp et al [ 17 ] noted that TikTok therapists, some with millions of followers, are actively providing corrective information to mental health misinformation and combatting mental health stigma on TikTok.

However, it is important to note that the videos in this sample were largely posted by consumers and not by health care professionals. Hence, further research is needed on the extent to which corrective mental health information is prevalent on popular mental health hashtags. Further, our findings indicate that health care professionals, particularly those who aim to provide corrective information, should be aware of and attend to both the video content and its related commentary.

Future Implications

Future research should focus on the potential role of intervention by health care professionals on social media. This would create changes for clinician practice, including raising issues related to the ethics of following patients online, concerns related to fake accounts, the user performance factor assumed as part of the TikTok platform, and mental health assessment of social media consumption [ 31 ]. As partnerships between health care professionals and social media platforms emerge, evaluation on effectiveness and best practices will be essential. Interestingly, the call for research related to greater understanding of TikTok health content creators, the integrity of the content, and user reaction and uptake to promote evidence-based information [ 35 ] to TikTok users may be contrary to the current appeal and need for accessible health-related resources that are different from mainstream medicine [ 12 ].

Limitations

The findings of this study offer insight into the use of TikTok to discuss mental health issues. However, this study is limited by the cross-sectional design. Further, the inclusion of English-only TikTok posts is limiting; videos posted in other languages may contribute to a more comprehensive understanding of the mental health conversations posted using the hashtag #mentalhealth. Other hashtags that specify a mental health illness or experience (suicide, anxiety, or depression) may have captured different videos than those captured by the generic use of hashtag #mentalhealth. Nonetheless, this study can serve as a foundation for further research to assess both the video content and its associated discussions, which are both important components to consider in studying mental health content on TikTok.

Multimedia Appendix 1

Multimedia appendix 2.

Conflicts of Interest: CHB serves as an Editorial Board Member for JMIR; she did not have a role in the review or editorial process for this article. All other authors declare no conflicts of interest.