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As social media networks become major channels for the diffusion of news and information, they are also increasingly targeted for abuse and manipulation. This talk overviews ongoing efforts in network analytics, data mining, and modeling to understand the spread of misinformation online and offline. Filippo Menczer of Indiana University will present machine learning methods to detect astroturf and social bots, as well as theoretical models to study how fake news and fact-checking compete for our collective attention. These efforts will be framed by a case study in which, ironically, his own research became the target of a coordinated disinformation campaign.
This work was conducted 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 by the National Science Foundation, McDonnell Foundation, Democracy Fund and Defense Advanced Research Projects Agency. 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.
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