Communications in Humanities Research ISSN: 2753-7072
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Research Article

Supportive and Risky Expressions in BiliBili Mental Health User-Generated Content

Chenyi HuangChengdu University*

* Corresponding author: [email protected]

Abstract

With the rapid growth of short-form and social video platforms, UGC has become a key channel for online mental health information, expression and support. BiliBili stands out in China for its community and interactivity. However, such content also carries risks including misinformation, stigma and emotional harm.This study investigates the production of mental health-related user-generated content (UGC) on Bilibili, focusing on two key dimensions: (1) how content creators construct positive and negative expressions through their videos, and (2) how viewers engage with these expressions in the comment and bullet comment sections. Through qualitative text analysis, this research interprets video materials, bullet comments, and user comments as intertwined texts ,, examining them in the context of theories on prosocial relationships, online social support systems, and platform diffusion mechanisms. This study argues that an essential element of BiliBili's mental health UGC is the 'duality' that it offers users: while it provides them information, empathy and companionship through the use of relatable stories, it also threatens to inculcate stigma, anxiety, to blur professional bounds in the provision of care, and intensify threat via algorithmic recommendation and community input. This paper aims to enhance case studies of mental health communication research conducted by Chinese platforms, thereby providing valuable insights for platform governance and content moderation.

Keywords: user-generated content (UGC); mental health; online social support; BiliBili
Published: June 23, 2026
DOI: 10.54254/2753-7064/2026.BJ34799
Volume: CHR Vol.114
pp. 42-48
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References

  1. Naslund, J. A., Bondre, A., Torous, J., & Aschbrenner, K. A. (2020). Social media and mental health: Benefits, risks, and opportunities for research and practice. Journal of Technology in Behavioral Science, 5(3), 245–257. https: //doi.org/10.1007/s41347-020-00134-x
  2. Wang, R. (2022). Community-building on Bilibili: The social impact of danmu comments. Media and Communication, 10(2), 54–65. https: //doi.org/10.17645/mac.v10i2.4996
  3. Chen, Y., Yin, J., Ding, Y., Wang, C., Zhu, J., & Niu, L. (2024). Evaluation of the quality of depression-related information on Chinese websites and video platforms: A cross-sectional comparative analysis. Frontiers in Psychiatry, 15. https: //doi.org/10.3389/fpsyt.2024.1408384
  4. Wang, G., Kuang, J., Qi, Y., & Li, J. (2025). Information quality of videos related to adolescent depression on social media platforms: A comparative study of TikTok and BiliBili. Frontiers in Public Health, 13. https: //doi.org/10.3389/fpubh.2025.1663977
  5. Naslund, J. A., Marsch, L. A., McHugo, G. J., & Bartels, S. J. (2016). The future of mental health care: Peer-to-peer support and social media. Epidemiology and Psychiatric Sciences, 25(2), 113–122. https: //doi.org/10.1017/S2045796015001067
  6. Starvaggi, I., Dierckman, C., & Lorenzo-Luaces, L. (2024). Mental health misinformation on social media: Review and future directions. Current Opinion in Psychology, 56. https: //doi.org/10.1016/j.copsyc.2023.101738
  7. Hoffner, C. A., & Bond, B. J. (2022). Parasocial relationships, social media, and well-being. Current Opinion in Psychology, 45. https: //doi.org/10.1016/j.copsyc.2022.101306
  8. Kysnes, B., Hjetland, G. J., Haug, E., Holsen, I., & Skogen, J. C. (2022). The association between sharing something difficult on social media and mental well-being among adolescents: Results from the "LifeOnSoMe" study. Frontiers in Public Health, 10. https: //doi.org/10.3389/fpubh.2022.1037888
  9. Zhang, Z., Reavley, N., Armstrong, G., & Morgan, A. (2025). Public disclosures of mental health problems on social media and audiences' self-reported anti-stigma effects. Health Promotion International, 40(1). https: //doi.org/10.1093/heapro/daae204
  10. Yao, Z., Ni, Z., Zhang, B., & Du, J. (2022). Do informational and emotional elements differ between online psychological and physiological disease communities in China? A comparative study of depression and diabetes. International Journal of Environmental Research and Public Health, 19(4), 2167. https: //doi.org/10.3390/ijerph19042167
  11. Samuel, L., Kuijpers, K., & Bleakley, A. (2024). TherapyTok for depression and anxiety: A quantitative content analysis of high engagement TikTok videos. Journal of Adolescent Health, 74(6), 1184–1190. https: //doi.org/10.1016/j.jadohealth.2024.02.002
  12. Armstrong, S., Osuch, E., Wammes, M., Chevalier, O., Kieffer, S., Meddaoui, M., & Rice, L. (2025). Self-diagnosis in the age of social media: A pilot study of youth entering mental health treatment for mood and anxiety disorders. Acta Psychologica, 256. https: //doi.org/10.1016/j.actpsy.2025.105015.
  13. Underhill, R., & Foulkes, L. (2025). Self-diagnosis of mental disorders: A qualitative study of attitudes on Reddit. Qualitative Health Research, 35(7), 779–792. https: //doi.org/10.1177/10497323241288785
  14. Vornholt, P., & De Choudhury, M. (2021). Understanding the role of social media-based mental health support among college students: Survey and Semistructured interviews. JMIR Mental Health, 8(7). https: //doi.org/10.2196/24512
  15. Weigle, P. E., & Shafi, R. M. A. (2024). Social media and youth mental health. Current Psychiatry Reports, 26(1), 1–8. https: //doi.org/10.1007/s11920-023-01478-w