On the Detection of Fake News, Conspiracy Theories, and Hate Speech Spreaders

Abstract

The rise of social media has offered a fast and easy way for the propagation of fake news and conspiracy theories. Despite the research attention that has received, fake news detection remains an open problem and users keep sharing texts that contain false statements. In this keynote I will describe how to go beyond textual information to detect fake news, taking into account also affective and visual information because providing important insights on how fake news spreaders aim at triggering certain emotions in the readers. I will also describe how psycholinguistic patterns and users' personality traits may play an important role in discriminating fake news spreaders from fact checkers. Finally, I will comment on some studies on the propagation of conspiracy theories. The ongoing work done on detection of disinformation, from fake news to conspiracy theories, is in the framework of IBERIFIER, the Iberian media research & fact-checking hub on disinformation funded by the European Digital Media Observatory (2020-EU-IA-0252), and the XAI-DisInfodemics project on eXplainable AI for disinformation and conspiracy detection during infodemics funded by the Spanish Ministry of Science and Innovation (PLEC2021-007681). In the final part of the keynote I will address also the other side of harmful information in social media, hate speech, making emphasis on the case of misogynous memes.