Countering the COVID-19 Misinfodemic with Text Similarity and Social Data Science
About this video
The Oxford Internet Institute is proud to present faculty member Dr Scott A. Hale for this session in our Wednesday Webinar Series. The session is moderated by Dr Chico Camargo, Postdoctoral Researcher in Data Science at the OII.
Misinformation about COVID-19 has led to severe harms in multiple instances: as an example, a rumor that drinking methanol would cure the virus resulted in hundreds of deaths. While end-to-end encryption is an important privacy safeguard, this encryption prevents platforms such as WhatsApp, Signal, and others from employing centralized interventions and warnings about misinformation. Several options, however, from user interface changes to tip lines to having more intelligence on client devices offer hope.
In this presentation Dr Scott A. Hale discusses how text similarity algorithms are being used to help fact-checkers locate misinformation, cluster similar misinformation, and identify existing fact-checks in the context of tip lines on platforms with end-to-end encryption. The presentation will detail research at the Oxford Internet Institute and Meedan, a global technology not-for-profit developing open-source tools for fact-checking and translation, that is actively being used by fact-checkers to improve the information available online.
About the Speakers
Senior Research Fellow, Programme Director of the MSc in Social Data Science
Dr Scott A. Hale is a Senior Research Fellow, Social Data Science MSc Programme Co-Director, and Turing Fellow. He develops and applies computer science techniques to the social sciences focusing on sociolinguistics, collective action, and misinformation.
Postdoctoral Researcher in Data Science
Dr Chico Camargo is an interdisciplinary researcher who develops and applies computational tools to study complex systems, collective human behaviour, public opinion dynamics and culture change.