Auditing TikTok’s recommendations: Understanding the prevalence of misinformation on the platform

Abstract

Short video platforms have rapidly increased in popularity, bringing forth a concerning trend: widespread dissemination of misinformation partially owing to the persuasive nature of the rich media these platforms support. However, little research has systematically investigated the role of algorithmic recommendations in this phenomenon. Our study addresses this gap by auditing the recommendation algorithm of TikTok, the leading short video platform, through four experiments. We explore the prevalence of misinformation in TikTok’s auto-complete suggestions, search results, and For You Page (FYP) recommendations. Our audits yielded a novel dataset comprising 8535 auto-complete suggestions, 160..