Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter

Abstract

The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success in motivating both recruitment and “lone wolf” attacks. The present work explores a large community of Twitter users whose activity supports ISIS propaganda diffusion in varying degrees. Within this ISIS supporting community, we observe a diverse range of actor types, including fighters, propagandists, recruiters, religious scholars, and unaffiliated sympathizers. The interaction between these users offers unique insight into the people and narratives critical to ISIS’ sustainment. In their entirety, we refer to this diverse set of users as an online extremist community or OEC. We present Iterative Vertex Clustering and Classification (IVCC), a scalable analytic approach for OEC detection in annotated heterogeneous networks, and provide an illustrative case study of an online community of over 22,000 Twitter users whose online behavior directly advocates support for ISIS or contibutes to the group’s propaganda dissemination through retweets.

Hateful People or Hateful Bots?

“…This nefarious use of bots is not new to social media; Ratkiewicz et al [43] indicated that bots have been used to amplify fake news and misinformation during the 2010 U.S. midterm elections through a coordinated generation and liking of misguiding tweets. It has also been shown that bots are used by ISIS propagandists to inflate their influence on Twitter and popularize their extreme ideologies [6,7].…”

“…In particular, any social media analysis that doesn't take into account the impact of bots is incomplete. While some bots can be beneficial (e.g., customer service chatbots), the focus in this work is on content-polluter bots that mimic human behavior online to spread falsified information [43], create a false sense of public support [9], and proliferate dangerous ideologies [6,7].…”

“…In our recent work on hate speech in Arabic social media [3,4], we showed that Arabic Twitter is awash with religious hatred which we defined as "a speech that is insulting, offensive, or hurtful and is intended to incite hate, discrimination, or violence against an individual or a group of people on the basis of religious beliefs or lack thereof". Having such a large volume of hate speech and knowing that ISIS and other radical organizations have been using bots to push their extreme ideologies [6,7], we hypothesize that bots may be to blame for a significant amount of this widespread hatred.…”

A complex networks approach to find latent clusters of terrorist groups

“…The multi-partite network which has been created and employed for our study relied on six main terrorist dimensions, namely: Events (N =41,456), Groups (N =1,493), Targets (N =22) [2] , Weapons (N =13) [3] , Tactics (N =9) [4] and operating Regions (N =12) [5] . These dimensions have been chosen because they represent the visible core of terrorist activity: the terror attack itself can indeed be represented by its perpetrator, the chosen target, the employed weapons and tactics and the geographic and political context in which it occurred.…”

“…Indeed, a recent stream of research has focused on the detection of terrorist or radical behaviors retrieving network-information from social media platforms. Social media allow to go beyond pure relational information, integrating instead geographical, temporal features and many other profile attributes to infer patterns and dynamics of extremist users [5,9,20,34].…”