Understanding “Fake News” in Research


Do you know how to recognise fake news? Register now to learn about "fake news" in research.

This webinar is targeted at beginners in fake news research and students/researchers who are eager to improve their skills in spotting fake news.


Given the recent proliferation of disinformation online, there has been also growing research interest in automatically debunking rumors, false claims, and “fake news”. A number of fact-checking initiatives have been launched so far, both manual and automatic, but the whole enterprise remains in a state of crisis: by the time a claim is finally fact-checked, it could have reached millions of users, and the harm caused could hardly be undone. An arguably more promising direction is to focus on fact-checking entire news outlets, which can be done in advance. Then, we could fact-check the news before they were even written: by checking how trustworthy the outlets that published them are.

Dr Nakov will show how this is done in Tanbih, a news aggregator that makes people aware of what they are reading. Tanbih features media profiles that show the general factuality of reporting, the degree of propagandistic content, hyper-partisanship, leading political ideology, general frame of reporting, stance with respect to various claims and topics, as well as audience reach and audience bias in social media.

Another important practical aspect that will be discussed is the use of specific propagandistic techniques that “fake news” articles rely on, e.g., appeal to emotions/prejudice/authority, logical fallacies, etc. Such techniques are essential for achieving the goals that “fake news” pursue, which offers a practical way to recognize them both for human users and for automatic tools.

Key Highlights:

  • Understand the various kinds of problems “fake news” pose to our society.
  • Learn how to detect websites that spread “fake news” and biased information. 
  • Learn about the propagandistic techniques that “fake news” critically rely on. 

Presenter(s)

Dr. Preslav Nakov - Principal Scientist, Qatar Computing Research Institute, Hamad Bin Khalifa University

Dr. Preslav Nakov

Principal Scientist, Qatar Computing Research Institute, Hamad Bin Khalifa University

Dr. Preslav Nakov is a Principal Scientist at the Qatar Computing Research Institute (QCRI), Hamad Bin Khalifa University (HBKU). His research interests include computational linguistics, “fake news” detection, fact-checking, machine translation, question answering, sentiment analysis, lexical semantics, Web as a corpus, and biomedical text processing. He received his PhD degree from the University of California at Berkeley (supported by a Fulbright grant), and he was a Research Fellow in the National University of Singapore, a honorary lecturer in the Sofia University, and research staff at the Bulgarian Academy of Sciences. At QCRI, he leads the Tanbih project, developed in collaboration with MIT, which aims to limit the effect of “fake news”, propaganda and media bias by making users aware of what they are reading. Dr. Nakov is the Secretary of ACL SIGLEX and of ACL SIGSLAV, and a member of the EACL advisory board. He is member of the editorial board of TACL, C&SL, NLE, AI Communications, and Frontiers in AI. He is also on the Editorial Board of the Language Science Press Book Series on Phraseology and Multiword Expressions. He co-authored a Morgan & Claypool book on Semantic Relations between Nominals, two books on computer algorithms, and many research papers in top-tier conferences and journals. He also received 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, MIT Technology Review, Science Daily, Popular Science, Fast Company, The Register, WIRED, and Engadget, among others.