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Social media users have long been aware of opaque content moderation systems and how they shape platform environments. On TikTok, creators increasingly utilize algospeak to circumvent unjust content restriction, meaning, they change or invent words to prevent TikTok’s content moderation algorithm from banning their video (e.g., “le$bean” for “lesbian”). We interviewed 19 TikTok creators about their motivations and practices of using algospeak in relation to their experience with TikTok’s content moderation. Participants largely anticipated how TikTok’s algorithm would read their videos, and used algospeak to evade unjustified content moderation while simultaneously ensuring target audiences can still find their videos. We identify non-contextuality, randomness, inaccuracy, and bias against marginalized communities as major issues regarding freedom of expression, equality of subjects, and support for communities of interest. Using algospeak, we argue for a need to improve contextually informed content moderation to valorize marginalized and tabooed audiovisual content on social media. 

Algospeak refers to social media users intentionally altering or substituting words when creating or sharing online content, for example, using ‘le$bean’ for ‘lesbian’. This study discusses the characteristics of algospeak as a computer-mediated language phenomenon on TikTok with regards to users’ algorithmic literacy and their awareness of how the platform’s algorithms work. We then present results from an interview study with TikTok creators on their motivations to utilize algospeak. Our results indicate that algospeak is used to oppose TikTok’s algorithmic moderation system in order to prevent unjust content violations and shadowbanning when posting about benign yet seemingly unwanted subjects on TikTok. In this, we find that although algospeak helps to prevent consequences, it often impedes the creation of quality content. We provide an adapted definition of algospeak and new insights into user-platform interactions in the context of algorithmic systems and algorithm awareness.