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- Title
Viralizar la verdad. Factores predictivos del engagement en el contenido verificado en TikTok.
- Authors
García-Marín, David; Salvat-Martinrey, Guiomar
- Abstract
Disinformation is one of the great challenges threatening the health of the public space and democratic systems, which must be based on truth to facilitate decision-making by citizens. For this reason, the fight against fake news has attracted attention from professionals and researchers during the last five years. In the journalistic field, numerous fact-checking outlets have been established. They use the media at their disposal and, above all, social networks to make verified content visible. TikTok, an emerging social video platform (very popular among the youth population), is the latest tool to be explored by fact-checkers to make the truth public. In this context, this paper aims to (1) determine the characteristics of fact-checkers' videos that drive their engagement on TikTok and (2) identify the factors that predict the number of likes, comments, views, times shared, and engagement rate of such content. All the videos published on this platform by the Spanish fact-checkers Maldito bulo and Newtral (n = 320) during the first 26 months of activity of both outlets were analyzed. Bivariate correlational studies, multiple linear regression, and binary logistic regression tests were applied. The type of content (verification versus explanation) has a greater impact on engagement than the topics of the videos. Verifications multiply the probability of a content getting an above-average number of likes, by 2.42. If the video is hosted by a woman, it doubles its chances of getting an above-average number of shares. Our results provide other valuable data that can help fact-checkers make their content more easily spreadable.
- Subjects
FAKE news; SOCIAL media; DEMOCRACY; LOGISTIC regression analysis; SOCIAL networks; DIGITAL video; DISINFORMATION; PUBLIC spaces
- Publication
El Profesional de la Información, 2022, Vol 31, Issue 2, p1
- ISSN
1386-6710
- Publication type
Article
- DOI
10.3145/epi.2022.mar.10