About this Event
For full information about the entire Disinformation conference, .
Deceptive, inaccurate, or misleading information can be spread intentionally (in an act of disinformation) or unintentionally (as misinformation). Being ill-informed is problematic for decision making either way, in most spheres of life, be it health, finances or politics. To aid human users with the identification of various kinds of problematic "fake" content, several methodologies have been developed in the fields Natural Language Processing (NLP)/Computational Linguistics, Machine Learning (ML), and Computer Science. Five large families of such systems include automated deception detectors, clickbait detectors, satirical fake detectors, rumor debunkers, and computational fact-checking tools. While computational literature documents their advances, these systems' existence is barely known outside of the experimental labs and their adoption is slow. This talk exemplifies representative methodologies, their success rates, and limitations. Given the viral nature and the scale of the problem, adoption of some form of automated detection systems is inevitable.
Victoria Rubin is a professor in the Faculty of Information and Media Studies at the University of Western Ontario, where she teaches graduate courses in the Library and Information Science Graduate Programs (MLIS and PhD LIS). As a researcher, she specializes in information retrieval and natural language processing techniques that enable analyses of texts to identify, extract, and organize structured knowledge. In her lab, LiT.RL, she and her students study complex human information behaviors that are, at least partly, expressed through language such as deception, uncertainty, credibility, and emotions. Her current focus is identifying misleading news with text analytics ). She has published widely on the use of AI to detect and prevent disinformation, including her recent book: Misinformation and Disinformation: Detecting Fakes with the Eye and AI. Dr. Rubin's research is unique in its identification of textual clues to disinformation in digital media, and her inclusion in this event is vital.
Event Venue & Nearby Stays
4TH SPACE, Concordia University, 1400 Maisonneuve Boulevard West, Montreal, Canada
CAD 0.00