Fighting the COVID-19 Infodemic: from Fake News to Harmful Content - Speaker: Preslav Nakov

The COVID-19 pandemic has brought us the first global infodemic. While fighting this infodemic is typically thought of in terms of factuality, the problem is much broader as malicious content includes not only „fake news“, rumors, and conspiracy theories, but also hate speech, racism, xenophobia, panic, and mistrust in authorities, among others. Thus, we argue for the need for a holistic approach combining the perspectives of journalists, fact-checkers, policymakers, social media platforms, and society as a whole, and we demonstrate how we model this in a practical system (

The infodemic is often described using terms such as „fake news“, which mislead people to focus exclusively on factuality, and to ignore the other half of the problem: the potential malicious intent. We aim to bridge this gap by focusing on the detection of specific propaganda techniques in text, e.g., appeal to emotions, fear, prejudices, logical fallacies, etc. We demonstrate a system for propaganda detection (, and we present the ongoing SemEval-2023 task 3 that focuses on detecting propaganda techniques and framing in English, French, German, Italian, Polish, and Russian. We further present extensions of this work to the automatic analysis of various types of harmful memes: from propaganda to harmfulness and harm’s target identification to role-labeling in terms of who is portrayed as hero/villain/victim, and generating natural text explanations.

Finally, we present a study of popular online platforms, and we point to the differences between what types of harmful content such platforms seek to curb and what researchers focus on.

Dr. Preslav Nakov is Professor at Mohamed bin Zayed University of Artificial Intelligence. Previously, he was a Principal Scientist at the Qatar Computing Research Institute (QCRI), HBKU, where he led the Tanbih mega-project, developed in collaboration with MIT, which aims to limit the impact of „fake news“, propaganda and media bias by making users aware of what they are reading, thus promoting media literacy and critical thinking. He received his PhD degree in Computer Science from the University of California at Berkeley, supported by a Fulbright grant. Dr. Preslav Nakov is President of ACL SIGLEX, Secretary of ACL SIGSLAV, Secretary of the Truth and Trust Online board of trustees, PC chair of ACL 2022, and a member of the EACL advisory board. He is also member of the editorial board of several journals including Computational Linguistics, TACL, ACM TOIS, IEEE TASL, IEEE TAC, CS&L, NLE, AI Communications, and Frontiers in AI. He authored a Morgan & Claypool book on Semantic Relations between Nominals, two books on computer algorithms, and 250+ research papers. He received a Best Paper Award at ACM WebSci’2022, a Best Long Paper Award at CIKM’2020, a Best Demo Paper Award (Honorable Mention) at ACL’2020, a Best Task Paper Award (Honorable Mention) at SemEval’2020, a Best Poster Award at SocInfo’2019, and the Young Researcher Award at RANLP’2011. He was also the first to receive the Bulgarian President’s John Atanasoff award, named after the inventor of the first automatic electronic digital computer. Dr. Nakov’s research was featured by over 100 news outlets, including Forbes, Boston Globe, Aljazeera, DefenseOne, Business Insider, MIT Technology Review, Science Daily, Popular Science, Fast Company, The Register, WIRED, and Engadget, among others.