Making Sense of Algorithm: Exploring TikTok Users’ Awareness of Content Recommendation and Moderation Algorithms

Abstract

This article examines algorithm awareness among young TikTok users, focusing on their understanding and experiences with the platform’s recommendation and moderation systems, and how these perceptions influence their engagement. Adopting a user-centric perspective, the study uses the vignette method with 50 young users across Italy to simulate scenarios involving TikTok’s algorithmic systems, aiming to uncover users’ algorithm awareness. The findings reveal that users interpret recommendation and moderation systems differently and engage with them critically based on these interpretations. Previous encounters with algorithmic systems, especially unexpected outcomes, enhance awareness of recommendation and moderation algorithms, fostering a more critical stance toward them.