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- articleJune 2018
Mining online communities to inform strategic messaging: practical methods to identify community-level insights
Computational & Mathematical Organization Theory (CMOT), Volume 24, Issue 2Pages 224–242https://doi.org/10.1007/s10588-017-9255-3The ability of OSNs to propagate civil unrest has been powerfully observed through the rise of the ISIS and the ongoing conflict in Crimea. As a result, the ability to understand and in some cases mitigate the effects of user communities promoting civil ...
- ArticleNovember 2016
Predicting Online Extremism, Content Adopters, and Interaction Reciprocity
AbstractWe present a machine learning framework that leverages a mixture of metadata, network, and temporal features to detect extremist users, and predict content adopters and interaction reciprocity in social media. We exploit a unique dataset ...
- research-articleOctober 2016
Who views online extremism? Individual attributes leading to exposure
Computers in Human Behavior (COHB), Volume 63, Issue CPages 311–320https://doi.org/10.1016/j.chb.2016.05.033Who is likely to view materials online maligning groups based on race, nationality, ethnicity, sexual orientation, gender, political views, immigration status, or religion? We use an online survey (Nź=ź1034) of youth and young adults recruited from a ...