Beyond Incitement to Violent Activity as Reflected in Social Media

• In Event: Communication, Social Media, and Terrorist Violence

Abstract

In this study, we utilize experimental software intended for the intelligence/policing communities to access the Facebook API and examine the radicalization on this platform. Our research is comprised of three unique analyses. In the first analysis we apply the Social Learning Theory and examine differences in online behaviors and activities between a sample of lone-wolf terrorists from Israel (N=30) and a matched group of non-terrorist radicals (N=30). In the second analysis we examine common public places, namely Pages and Groups that were identified in the first analysis. Here we examine differences in behaviors and interactions between the most active members and the less active members in order to identify how differences in such activity may be used to predict a user's position on the radicalization spectrum. In the third analyses, we examine how NSM traffic and activity, in the form of hashtags, keywords/phrases and specific shares (identified in the first two analyses) may be used to predict real-world terrorism events. We conduct fixed and random effects models to determine if the NSM traffic can predict attacks such as those that occurred in the 2015 wave of lone-wolf terrorism in Israel.

Authors

• Simon Perry, Hebrew University, Israel

• Badi Hasisi, Hebrew University