Michael Ann DeVito, CU Department of Information Science

Social platforms open important doors to visibility for transgender people, through which we can pursue key goals such as securing recognition and acceptance, building community and providing mutual aid. However, each door to visibility is also potentially a trap, filled with risks and consequences including serious and sustained campaigns of harassment. These visibility-related risks are heightened for transfeminine content creators who are often targeted for mass harassment on transphobic, misogynistic and transmisogynistic grounds. However, many pro-social goals require visibility, and some transfeminine content creators choose to try and navigate algorithmic doors to visibility despite the risks of algorithmic traps. In this talk, I will present recent work I conducted as a member-researcher in my own community of transfeminine Tiktok creators. I will illustrate how transfeminine TikTok creators with pro-social, visibility-requiring goals navigate this landscape of algorithmic doors and their associated traps by the light of folk theorization. I will discuss how transfeminine creators employ multiple complex and overlapping folk theories to guide high-stakes decision making and introduce a practically-focused extension of my folk theorization framework into actionable and demotivational folk theories. Along the way, I will introduce five novel folk theories of TikTok spanning both the For You Page and content moderation systems, and discuss how two cross-cutting issues, perceived algorithmic paternalism and decontextualization, illustrate major issues for transfeminine creators and opportunities for more supportive design.

 Refreshments will be served in the INFO building directly following the talk.

Bio: Dr. Michael Ann DeVito is a postdoctoral Computing Innovation Fellow in the Department of Information Science at the University of Colorado Boulder. She is a qualitative researcher who studies how users and communities understand and adapt to the challenges of everyday, casual human/AI collaboration. This includes work on folk understandings of algorithms, as well as work as a member-researcher on how queer and trans communities adapt to social platforms. Dr. DeVito earned a PhD in Media, Technology, and Society from Northwestern University. She frequently publishes in and organizes for ACM conferences such as CSCW and CHI.