Making Sense of Digital Content Moderation from the Margins
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This dissertation, Making Sense of Digital Content Moderation from the Margins, examines how content creators who are marginalized by race, sexuality, gender, ethnicity, and disability understand their experiences of content moderation on the social media platform TikTok. Using critical interface and narrative-based inquiry methods with six marginalized content creators on TikTok, I argue that marginalized creators navigate the opaque content moderation infrastructure of TikTok by drawing on their embodied experiences. The key research questions ask how these content creators interpret TikTok's platform policies and processes through their interactions on the app and how these interpretations influence content creation on TikTok and how creators feel about moderation in the absence of platform transparency about how content is moderated. To answer these questions, I conducted narrative-driven interviews with six TikTok creators and analyzed these stories alongside online testimonials in eight Change.org petitions. My analysis revealed that lack of transparency around TikTok's algorithmic curation and moderation contributes to content creators feeling alienated, exploited, frustrated, and unwelcome on the platform and influences content creators to adapt their content to avoid moderation, oftentimes by self-censoring themselves and aspects of their marginalized identities. Over time, the accumulation of content moderation micro-interactions diminishes the ability of marginalized content creators to trust content moderation processes. My analysis also shows how TikTok's user experience design and opaque content moderation practices contribute to an affective platform environment in which creators are compelled to speak out and across creator networks about such gaps in experience and platform policy. I conclude with a discussion of how my findings about content moderation and transparency contribute to conversations in writing-related scholarship, especially as it pertains to writing assessment, technical communication, and algorithmic research methodologies.