Dynamics of algorithmic content amplification on TikTok

Abstract Content exposure online is increasingly shaped by socio-technical systems, where human and algorithmic factors interact. TikTok exemplifies strong algorithm-driven curation, tailoring the stream of content towards users’ interests based on their behavior on the platform. Despite growing concerns about TikTok’s societal impact, the dynamics of content amplification at the individual level remain largely unquantified. How quickly, and to what extent, does TikTok amplify content aligned with users’ interests? To address these questions, we conduct a sock-puppet audit, deploying bots with different interests to engage with TikTok’s “For You” feed. Our findings reveal that content aligned with the bots’…

• MF
  Max-Planck-Institut für Bildungsforschung