Algorithmic Curation and Its Effects on LGBTQ Youth Civic Engagement
This study examines how TikTok’s algorithmic recommendation system shapes the visibility of civic and political content among young LGBTQ+ users. Drawing from a dataset of 1,000 TikTok videos, it models algorithmic curation (e.g., the TikTok “For You” page) as a process that both personalizes and fragments exposure to civic discourse. By first dividing LGBTQ+ youth TikTok users into twenty distinct ‘personas’ (a methodology common in this field of algorithmic analysis) — from “Policy Nerd Gen Z” to “First-Time Voter” — and then simulating “For You” feeds for each of them, this study reveals that civic content on TikTok is (1) unevenly distributed to young LGBTQ+ users, and (2) selectively clustered away from users who TikTok labels as less visibly tied to their queer identity or less “political.”