Dr. Preslav Nakov
Monday 02:00 PM, January 9th, 2023
Multimodal fake news detection
Multimodal Fake News Detection: While initially primarily text-based, fake news has been getting increasingly multimodal, involving images (e.g., in memes), speech, and video. I will describe work on fact-checking real-world claims made in the context of political debates using both the textual and the speech modality. I will further cover some tasks that can support journalists and fact-checkers in their work such as analyzing political debates, speeches or live interviews, and spotting interesting claims to fact-check as well as detecting claims that have been fact-checked already (the latter would allow the journalist/moderator to put the politician on the spot in real time when the politician repeats a known lie), where the speech and the textual modality can complement each other. Finally, I will discuss profiling entire news outlets for their factuality and bias (which allows to detect the fake news before it was even written, by checking how trustworthy the outlet that has published it is, which is what journalists actually do), based on what they write, on how users react to that, but also on the multimodal content they use, e.g., the speech signal in the videos they post, which allows to model not only what was said, but also how it was said.
Dr. Preslav Nakov is Professor and Acting Deputy Department Chair at the Natural Language Processing department of Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). His current research focuses on detecting and understanding disinformation, propaganda, fake news, and media bias. Previously, he was a Principal Scientist at the Qatar Computing Research Institute, 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, and member of the EACL advisory board; he was also a PC chair of ACL 2022. He is a 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 for work on propaganda and coordinated community detection, a best paper award at CIKM 2020 for work on fake news detection in social media, a best demo paper award (honorable mention) at ACL 2020 and a best task paper award (honorable mention) at SemEval 2020, both for work on detecting propaganda techniques in text, as well as a 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 MIT Technology Review, CACM Research Highlights, Forbes, Boston Globe, Al Jazeera, Science Daily, Popular Science, Fast Company, The Register, WIRED, and Engadget.