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ABSTRACT
Fake news has become a threat to the stability of electoral processes in the last years, spreading through decentralised and fragmented infrastructures of digital platforms. This study examines the characteristics of digital accounts that published fake news stories on social media in the 2018 Brazilian presidential elections, taking into account the type, relevance and propensity of robotisation of 1073 users. The study shows that fake news stories are disseminated more by personal profiles than by pages, and that most parts of the principal spreaders presented highly relevant performance, the vast majority being Facebook accounts and a reasonable slice of Twitter. The most relevant accounts in the fake news spreading on Facebook and Twitter were classified as: “not bot-like” and “not bot”, while those framed as “bot-like” or “not possible to assert” had 4.7 times less sharing. This research also shows that fake news spreading cannot be explained mainly by the use of bots, especially in elections.
Acknowledgements
This paper uses part of the methodology and empirical analysis of the author’s doctoral thesis financed by the Coordination for the Improvement of Higher Education Personnel of Brazil.
Disclosure Statement
No potential conflict of interest was reported by the author(s).
Notes
1 Pega Bot’s methodology is available at: https://pegabot.com.br.
2 Botometer’project and methodology are available at https://botometer.osome.iu.edu/faq.