Exploring the Antecedents of Social Media Fatigue in the Context of Interactive Behaviours

Authors

  • Xinran Hu Department of Media and Communication, Xi'an Jiaotong-Liverpool University, Suzhou, China Author

DOI:

https://doi.org/10.71222/134bya36

Keywords:

social media fatigue, interactive behaviours, cross-platform usage, interaction quality, system feature overload, social network density

Abstract

The pervasive integration of social media into daily life has been accompanied by a growing sense of exhaustion and disengagement among users, a phenomenon widely recognized as social media fatigue. While existing research has extensively explored causes such as information overload and privacy concerns, there remains a scarcity of studies that systematically investigate the specific role of interactive behaviours in driving this fatigue. To address this gap, this study develops and tests a multi-dimensional framework integrating Uses and Gratifications Theory, the Technology Acceptance Model, and Social Network Analysis to examine how factors at the individual, platform, and social levels contribute to fatigue. Data were collected via an online survey from 150 active Chinese social media users. The results from regression analysis reveal that cross-platform social media usage, system feature overload, and social network density are significant positive predictors of social media fatigue. Conversely, the quality of social interactions exhibits a significant negative relationship with fatigue, suggesting that meaningful engagement can serve as a buffer. However, the frequency of using instant messaging platforms and participation in group interactions did not show a significant direct effect. These findings offer a nuanced understanding of the mechanisms behind social media fatigue, shifting the focus from mere usage volume to the nature and structure of interactions. The study provides valuable empirical evidence for platform designers and policymakers aiming to mitigate user burnout by optimizing interface simplicity, managing cross-platform cognitive load, and fostering higher-quality digital communication environments.

References

1. H. Zheng, and R. Ling, "Drivers of social media fatigue: A systematic review," Telematics and informatics, vol. 64, p. 101696, 2021. doi: 10.1016/j.tele.2021.101696

2. T. Ravindran, A. C. Yeow Kuan, and D. G. Hoe Lian, "Antecedents and effects of social network fatigue," Journal of the Association for Information Science and Technology, vol. 65, no. 11, pp. 2306-2320, 2014. doi: 10.1002/asi.23122

3. A. Dhir, Y. Yossatorn, P. Kaur, and S. Chen, "Online social media fatigue and psychological wellbeing-A study of compulsive use, fear of missing out, fatigue, anxiety and depression," International journal of information management, vol. 40, pp. 141-152, 2018. doi: 10.1016/j.ijinfomgt.2018.01.012

4. K. T. Yeung, "What does love mean? Exploring network culture in two network settings," Social Forces, vol. 84, no. 1, pp. 391-420, 2005.

5. S. Pradhan, "Social network fatigue: revisiting the antecedents and consequences," Online Information Review, vol. 46, no. 6, pp. 1115-1131, 2022. doi: 10.1108/oir-10-2020-0474

6. L. F. Bright, S. B. Kleiser, and S. L. Grau, "Too much Facebook? An exploratory examination of social media fatigue," Computers in human behavior, vol. 44, pp. 148-155, 2015. doi: 10.1016/j.chb.2014.11.048

7. M. Griffith, and E. Seidman, "Understanding media: The extensions of man," 1968. doi: 10.2307/355246

8. P. Verduyn, O. Ybarra, M. Résibois, J. Jonides, and E. Kross, "Do social network sites enhance or undermine subjective wellbeing? A critical review," Social Issues and Policy Review, vol. 11, no. 1, pp. 274-302, 2017. doi: 10.1111/sipr.12033

9. S. Fu, H. Li, Y. Liu, H. Pirkkalainen, and M. Salo, "Social media overload, exhaustion, and use discontinuance: Examining the effects of information overload, system feature overload, and social overload," Information Processing & Management, vol. 57, no. 6, p. 102307, 2020. doi: 10.1016/j.ipm.2020.102307

10. J. Chauhan, M. S. Ansari, M. Taqi, and M. Ajmal, "Dividend policy and its impact on performance of Indian information technology companies," International Journal of Finance and Accounting, vol. 8, no. 1, pp. 36-42, 2019.

11. A. Dhir, P. Kaur, S. Chen, and S. Pallesen, "Antecedents and consequences of social media fatigue," International Journal of Information Management, vol. 48, pp. 193-202, 2019. doi: 10.1016/j.ijinfomgt.2019.05.021

12. X. Zhu, and Z. Bao, "Why people use social networking sites passively: An empirical study integrating impression management concern, privacy concern, and SNS fatigue," Aslib Journal of Information Management, vol. 70, no. 2, pp. 158-175, 2018.

13. E. M. Cramer, H. Song, and A. M. Drent, "Social comparison on Facebook: Motivation, affective consequences, self-esteem, and Facebook fatigue," Computers in Human Behavior, vol. 64, pp. 739-746, 2016. doi: 10.1016/j.chb.2016.07.049

14. A. N. Islam, S. Laato, S. Talukder, and E. Sutinen, "Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive load perspective," Technological forecasting and social change, vol. 159, p. 120201, 2020. doi: 10.1016/j.techfore.2020.120201

15. S. MEYER, "What is a GRAT?," .

16. E. Lee, K. Y. Lee, Y. Sung, and Y. A. Song, "# DeleteFacebook: antecedents of Facebook fatigue," Cyberpsychology, Behavior, and Social Networking, vol. 22, no. 6, pp. 417-422, 2019.

17. A. E. Marwick, and D. Boyd, "I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience," New media & society, vol. 13, no. 1, pp. 114-133, 2011.

18. R. S. Burt, "The network structure of social capital," Research in organizational behavior, vol. 22, pp. 345-423, 2000. doi: 10.1016/s0191-3085(00)22009-1

19. E. Katz, J. G. Blumler, and M. Gurevitch, "Uses and gratifications research," The public opinion quarterly, vol. 37, no. 4, pp. 509-523, 1973.

20. F. D. Davis, "Perceived usefulness, perceived ease of use, and user acceptance of information technology," MIS quarterly, pp. 319-340, 1989. doi: 10.2307/249008

21. S. Wasserman, "Social network analysis: Methods and applications," The Press Syndicate of the University of Cambridge, 1994. doi: 10.2307/3322457

22. C. Qin, Y. Li, T. Wang, J. Zhao, L. Tong, J. Yang, and Y. Liu, "Too much social media? Unveiling the effects of determinants in social media fatigue," Frontiers in psychology, vol. 15, p. 1277846, 2024. doi: 10.3389/fpsyg.2024.1277846

23. L. Teng, D. Liu, and J. Luo, "Explicating user negative behavior toward social media: an exploratory examination based on stressor-strain-outcome model," Cognition, Technology & Work, vol. 24, no. 1, pp. 183-194, 2022. doi: 10.1007/s10111-021-00665-0

24. S. Zhang, L. Zhao, Y. Lu, and J. Yang, "Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services," Information & management, vol. 53, no. 7, pp. 904-914, 2016. doi: 10.1016/j.im.2016.03.006

25. Z. Kong, X. Zhang, and R. Wang, "Review of the research on the relationship between algorithmic news recommendation and information cocoons," In 2021 3rd International Conference on Literature, Art and Human Development (ICLAHD 2021), November, 2021, pp. 341-345.

26. A. Bergström, and M. Jervelycke Belfrage, "News in social media: Incidental consumption and the role of opinion leaders," Digital journalism, vol. 6, no. 5, pp. 583-598, 2018.

27. A. Nadkarni, and S. G. Hofmann, "Why do people use Facebook?," Personality and individual differences, vol. 52, no. 3, pp. 243-249, 2012. doi: 10.1016/j.paid.2011.11.007

28. M. Ou, H. Zheng, H. K. Kim, and X. Chen, "A meta-analysis of social media fatigue: Drivers and a major consequence," Computers in Human Behavior, vol. 140, p. 107597, 2023. doi: 10.1016/j.chb.2022.107597

29. H. Pang, M. Ji, and X. Hu, "How differential dimensions of social media overload influences young people's fatigue and negative coping during prolonged COVID-19 pandemic? Insights from a technostress perspective," In Healthcare, December, 2022, p. 6. doi: 10.3390/healthcare11010006

30. A. M. Rubin, "Television uses and gratifications: The interactions of viewing patterns and motivations," Journal of broadcasting & electronic media, vol. 27, no. 1, pp. 37-51, 1983. doi: 10.1080/08838158309386471

31. I. EDUCATION, "BILDUNG IN THE DIGITAL AGE," .

32. H. H. Alharahsheh, and A. Pius, "A review of key paradigms: Positivism VS interpretivism," Global academic journal of humanities and social sciences, vol. 2, no. 3, pp. 39-43, 2020.

33. A. Bryman, "Social research methods," Oxford university press, 2016.

34. M. Z. Reyes, "Social research: A deductive approach," Rex Bookstore, Inc, 2004.

35. A. Fink, "The survey handbook," sage, 2003. doi: 10.4135/9781412986328

36. A. Field, "Discovering statistics using IBM SPSS statistics," Sage publications limited, 2024.

37. C. Andrade, "The P value and statistical significance: misunderstandings, explanations, challenges, and alternatives," Indian journal of psychological medicine, vol. 41, no. 3, pp. 210-215, 2019. doi: 10.4103/ijpsym.ijpsym_193_19

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Published

26 November 2025

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How to Cite

Hu, X. (2025). Exploring the Antecedents of Social Media Fatigue in the Context of Interactive Behaviours. Journal of Media, Journalism & Communication Studies, 1(1), 138-151. https://doi.org/10.71222/134bya36