This Working Group is comprised of a team of computational social scientists, psychologists, and public health specialists who specialize in the analysis of social media data and machine learning. The group predicts the spread of COVID-19 disinformation in social media networks. Leveraging social science, public health, and computer science, it will correlate group-level psychological traits with the willingness to spread disinformation related to COVID-19 across social media.
Social Media Data, Machine Learning, and Predicting Online Disinformation Propagation
Working Group Lead
David Muchlinski, Georgia Institute of Technology
Working Group Members
Rebecca Christofferson, Louisiana State University
Courtney Crooks, Georgia Institute of Technology
Munmun De Choudhury, Georgia Institute of Technology
Nadine Kaslow, Emory University
CONVERGE is funded by the National Science Foundation (NSF), Division of Civil, Mechanical, and Manufacturing Innovation, Program on Humans, Disasters, and the Built Environment (Award #1841338). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.