Tackling disinformation is an inherently inter-disciplinary question. At MIT, researchers have understood disinformation proliferation and detection through experimental methods in psychology, natural language techniques, graph networks analysis, media forensics, data sharing and more. When encountering misinformation, the average person is challenged to make several decisions ranging from those that determine the veracity of piece of information to those that determine whether the potentially misleading information should be shared or not. When making these decisions, individuals are influenced by extant political and social biases, heuristics (mental shortcuts), personal reasoning and reflection, and the design of platforms and channels that they use to communicate. Further, the information that is misleading could be visual, textual, auditory or multi-modal. The diversity in the kinds of information that is created, shared, and consumed and the potential for large-scale proliferation and harm (at the social, political, and environmental level) from such information necessitate an interdisciplinary inquiry into the disinformation problem.

Dealing with this, and similar, paradoxical aspects of human failings (as related to processing information) motivates this seminar series. The series hosts disinformation scholars with diverse expertise to present their understanding and research on the issue. The goal of the seminar series is to spark conversations and collaborations, and inspire new research questions into understanding and tackling disinformation.


All talks will be held in 32-D507 from 4PM - 5PM EST.

Please register for Zoom access.

Date Speaker Affiliation Topic Links
Mar 31 Rahul Bhui MIT Sloan Paradoxical effects of persuasive messages Recording, Paper, Slides
Apr 14 Mohsen Mosleh MIT Sloan/BCS Understanding and reducing the spread of misinformation online Recording; Papers 1, 2, 3, 4; Slides
Apr 28 Kiran Garimella Rutgers University Content moderation on encrypted platforms
May 12 Max Tegmark MIT Physics Machine-learning media bias
May 19 Elzbieta Drazkiewicz Slovak Academy of Sciences Studying conspiracy theories with compassion
May 26 Adam Berinsky MIT Political Science Understanding and Reducing Online Misinformation Across 16 Countries on Six Continents
Jun 2 Aleksandra Korolova University of Southern California Auditing the hidden societal impacts of ad delivery algorithms
June 9 Preslav Nakov QCRI Detecting the "Fake News" Before It Was Even Written, Media Literacy, and Flattening the Curve of the COVID-19 Infodemic
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