Chapter in a collection edited by Jorge Vázquez-Herrero, María-Cruz Negreira-Rey and Ana-Isabel Rodríguez-Vázquez on journalism on TikTok, with the participation of coLAB researchers.
BOOK SYNOPSIS This book offers a pioneering contribution to the scholarly exploration of journalism on TikTok, a social media platform that has become increasingly central to the contemporary media landscape. As media platformization advances, news outlets and journalists have entered a space defined by algorithmic recommendation and virality, adapting to its logic, affordances, formats, trends, and audiences. This volume features 31 chapters structured into five sections: Understanding and researching TikTok journalism; News media outlets; Journalists; Audience and public sphere; and Information disorders and fact-checking. Bringing together contributions from 58 scholars across 15 countries, the book provides a critical and timely overview of the ongoing transformations of TikTok journalism.
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CHAGAS, V. The Algorithmic Trap: How Hyperpartisan Media Pose a Risk to News Consumption in TikTok’s Recommendation System. In: VÁZQUEZ-HERRERO, J.; NEGREIRA-REY, M.-C.; RODRÍGUEZ-VÁZQUEZ, A.-I. (Ed.). TikTok Journalism: News, Media, and Journalists in the Short Video Era. Berlin: Peter Lang, 2024.