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’ interests undergoes strong amplification, with rapid reinforcement typically occurring within the first 200 videos watched. While amplification is consistently observed across all interests, its intensity and dynamics vary, as revealed by time series analyses and Markov models. Although TikTok’s algorithm preserves some content diversity, we find a strong negative correlation between amplification and exploration: as the amplification of interest-aligned content increases, the diversity of encountered hashtags declines sharply. Our findings contribute to discussions on socio-algorithmic feedback loops in the digital age and the trade-offs between personalization and content diversity.
Baumann et al. (Wed,) studied this question.