Queering algorithms: LGBTQ+ content creators’ non-conforming and non-confronting workarounds to digital normativity in China

Popular social media platforms in China, such as Bilibili, Douyin, and Xiaohongshu (REDnote), use machine learning algorithms to curate personalized feeds and enforce content moderation. But the opacity of such algorithms introduces socially consequential and often problematic mechanisms of classification. Given the playful resistance of queer individuals against a normative social environment, the interaction between algorithms and content creators warrants close examination. This study investigates how LGBTQ+ content creators navigate these algorithm-driven platforms, focusing on their negotiation of digital normativity to share non-heterosexual content and foster queer sociality in China. Avoiding the oversimplification of viewing algorithms and those implementing them as monolithic entities, I explore how content creators creatively manage to produce and distribute their work within the constraints of these platforms, and even by playing with these constraints. I collected data from an ethnography on algorithms, interviews, and an open-source investigation into recommendation algorithms, through a scavenge approach. I argue that LGBTQ+ content creators engage with algorithms in ways that are simultaneously non-conforming and non-confrontational. They imagine algorithmic effects, appropriate outcomes, and play with the opacity of machine learning to navigate three aspects of digital normativity in China: heteronormativity, Internet civilization, and commercialization. Empirically, I identified three strategies used to create and expand queer sociality within these constraints: camouflaging, filtering, and verticalizing. Theoretically, I introduce ‘workarounds’ as a framework that transcends the binary perspectives of conformity and resistance in discussions of authoritarian governance, algorithmic control, and user-platform interaction.