Social media platforms are a place where people look for information and social support for mental health, resulting in both positive and negative effects on users. TikTok has gained notoriety for an abundance of mental health content and discourse.We present findings from a semi-structured interview study with 16 participants about mental health content and participants’ perceptions of community on TikTok. We find that TikTok’s community structure is permeable, allowing for self-discovery and understanding not found in traditional online communities. However, participants are wary of mental health information due to conflicts between a creator’s vulnerability and credibility. Our interviews suggest that the “For You Page” is a runaway train that encourages diverse community and content engagement but also displays harmful content that participants feel they cannot escape. We propose design implications to support better mental health, as well as implications for social computing research on community in algorithmic landscapes.
Ashlee Milton, Leah Ajmani, Michael Ann DeVito, and Stevie Chancellor. 2023. “I See Me Here”: Mental Health Content, Community, and Algorithmic Curation on TikTok. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23), April 23–28, 2023, Hamburg, Germany. ACM, New York, NY, USA, 17 pages. https://doi.org/10.1145/3544548.358148