Unraveling Entangled Feeds: Rethinking Social Media Design to Enhance User Well-being

要旨

Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design workshops with 21 participants diagnosed with mental illness about their interactions with social media platforms. We find that users develop cause-and-effect explanations, or folk theories, to understand their experiences with algorithmic curation. These folk theories highlight a breakdown in algorithmic design that we explain using the framework of entanglement, a phenomenon where there is a disconnect between users' actions and platform outcomes on an emotional level. Participants' designs to address entanglement and mitigate harms centered on contextualizing their engagement and restoring explicit user control on social media. The conceptualization of entanglement and the resulting design recommendations have implications for social computing and recommender systems research, particularly in evaluating and designing social media platforms that support users' mental well-being.

著者
Ashlee Milton
University of Minnesota, Minneapolis, Minnesota, United States
Daniel Runningen
University of Minnesota, Minneapolis, Minnesota, United States
Loren Terveen
University of Minnesota, Minneapolis, Minnesota, United States
Harmanpreet Kaur
University of Minnesota, Minneapolis, Minnesota, United States
Stevie Chancellor
University of Minnesota, Minneapolis, Minnesota, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Social Media Feeds and Algorithms

P1 - Room 114
7 件の発表
2026-04-16 18:00:00
2026-04-16 19:30:00