Disinformation and vaccines on social networks: Behavior of hoaxes on Twitter
Author/s
Noguera Vivo, Jose Manuel; Grandío Pérez, María del Mar; Villar Rodríguez, Guillermo; Martín, Alejandro; Camacho, DavidDate
2023Discipline/s
Ciencias de la ComunicaciónSubject/s
DisinformationHoaxes
Vaccines
Artificial Intelligence
Health Information
Abstract
Anti-vaccine disinformation is highly dangerous due to its direct effects on society.
Although there is relevant research on typologies of hoaxes, denialist discourses on networks, or the
popularity of vaccines, this study provides a complementary and pioneering vision about the antivaccine discourse of COVID-19 on Twitter, focused on its spreaders’ behavior. Methodology: Given
an initial sample of a hundred hoaxes (from December 2020 to September 2021) for the download
of 200,246 tweets, around 36,000 tweets (N=36.292) that support or deny disinformation have been
filtered through an algorithm for Natural Language Inference (NLI) to analyze their spreaders’ through
their metrics in the platform. Results: In relative numbers, the results show, among others, more
hoaxes with original content (not retweets) among accounts with more followers and those verified;
more irruption of disinformation as opposed to its objection by accounts created between 2013 and
2020, and the associa...