Authors
Daniel Delmonaco, Samuel Mayworm, Hibby Thach, Josh Guberman, Aurelia Augusta, Oliver L Haimson
Publication date
2024/4/23
Journal
Proceedings of the ACM on Human-Computer Interaction
Volume
8
Issue
CSCW1
Pages
1-39
Publisher
ACM
Description
Shadowbanning is a unique content moderation strategy receiving recent media attention for the ways it impacts marginalized social media users and communities. Social media companies often deny this content moderation practice despite user experiences online. In this paper, we use qualitative surveys and interviews to understand how marginalized social media users make sense of shadowbanning, develop folk theories about shadowbanning, and attempt to prove its occurrence. We find that marginalized social media users collaboratively develop and test algorithmic folk theories to make sense of their unclear experiences with shadowbanning. Participants reported direct consequences of shadowbanning, including frustration, decreased engagement, the inability to post specific content, and potential financial implications. They reported holding negative perceptions of platforms where they experienced …
Total citations
Scholar articles
D Delmonaco, S Mayworm, H Thach, J Guberman… - Proceedings of the ACM on Human-Computer …, 2024