Vulnerable, threat and influencer characterisation for radicalisation risk assessment

Abstract

ABSTRACT Past work on key actor detection in the area of terrorism typically focuses on the identification of Threats i.e. users with overt radical signals, or Influencers i.e. users who communicate a high volume of tweets and receive a high volume of replies from their followers. In this work, we expanded the detection of key actors to include Vulnerables, Threats and Influencers who displayed consistent behaviours and incorporated the social-level metrics between these actors to assess potential for radicalisation. Through a Twitter Analytic Pipeline which comprised a bot detector, psychological language analysis, stance detector, and social network analysis modules, we detected 14,246 Vulnerables, 25,704 Threats, and 430 Influencers out of a total of 166,653 users in Twitter conversations on the 2020 France terror attacks. A network of 570 users were identified as accounts of interest, demonstrating the utility of this approach in streamlining the detection of persistent, high-ranking Influencers and Threats while contributing to the identification of early risk signals exhibited by Vulnerables.