Reception and resistance in response to fake news corrections in the pandemic: the experience of robot Fátima, from Aos Fatos agency, on Twitter

Abstract

Fact-checking agencies face the challenge of making their checks reach audiences who are unaware, suspicious or hostile to their verification methods. Social networks, a space in which fake news proliferates, can also expand the public of these agencies. This article evaluates the experience of an automated Twitter account created by Aos Fatos agency to identify and interact with users of this social network who publish false information. The robot dubbed “Fátima” scans Twitter to identify posts with links that have already been refuted by the verification agency, and responds to users indicating the error and its correction. This survey seeks to assess which false news was most frequent during the pandemic in 2020, and how users interacted in response to these corrections.