Overview of the 8th Author Profiling Task at PAN 2020: Profiling Fake News Spreaders on Twitter

Abstract

[EN] This overview presents the Author Profiling shared task at PAN 2020. The focus of this year's task is on determining whether or not the author of a Twitter feed is keen to spread fake news. Two have been the main aims: (i) to show the feasibility of automatically identifying potential fake news spreaders in Twitter; and (ii) to show the difficulty of identifying them when they do not limit themselves to just retweet domain-specific news. For this purpose a corpus with Twitter data has been provided, covering the English and Spanish languages. Altogether, the approaches of 66 participants have been evaluated.First of all we thank the participants: 66 this year, record in terms of participants at PAN Lab since 2009! We have to thank also Martin Potthast, Matti Wiegmann, and Nikolay Kolyada to help with the 66 Virtual Machines in the TIRA platform. We thank Symanto for sponsoring the ex aequo award for the two best performing systems at the author profiling shared task of this year. The work of Paolo Rosso was partially funded by the Spanish MICINN under the research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech (PGC2018-096212-B-C31). The work of Anastasia Giachanou is supported by the SNSF Early Postdoc Mobility grant under the project Early Fake News Detection on Social Media, Switzerland (P2TIP2 181441).Rangel, F.; Giachanou, A.; Ghanem, BHH.; Rosso, P. (2020). Overview of the 8th Author Profiling Task at PAN 2020: Profiling Fake News Spreaders on Twitter. CEUR Workshop Proceedings. 2696:1-18. http://hdl.handle.net/10251/166528S118269