As social media become major channels for the diffusion of news and information, it becomes critical to understand how the complex interplay between cognitive, social, and algorithmic biases triggered by our reliance on social networks makes us vulnerable to disinformation. This talk overviews ongoing network analytics, modeling, and machine learning efforts to study the viral spread of misinformation and to develop tools for countering the online manipulation of opinions.
Joint work with collaborators at the Center for Complex Networks and Systems Research (cnets.indiana.edu) and the Indiana University Network Science Institute (iuni.iu.edu). This research is supported in part by the National Science Foundation, McDonnell Foundation, DARPA, Yahoo, and Democracy Fund. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of these funding agencies.
Speaker: Filippo Meczner, University of Indiana