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Any intervention in the violent acts of terrorist groups requires accurate differentiation among the groups themselves, which has largely been overlooked in their study beyond qualitative work. To explore the notion of terrorist group differentiation, the online communication of six violent groups were collected: Al-Nusrah Front, al-Qa’ida Central, al-Qa’ida in the Arabian Peninsula, Hamas, Islamic State of Iraq and Syria, and Taliban. All six groups embedded their ideology in digitised documents that were shared through multiple online social networks and media platforms in attempts to influence individuals to identify with their beliefs. The way these groups constructed social roles for their supporters in their ideology was proposed as a novel way to differentiate them and key term extraction was used to find important terms referenced in their communication. Experimental classification was devised to find the highest-ranking roles capable of prediction. Role terms produced high accuracy scores across experiments differentiating the groups (95%CI: 95–98%), with varying inter-group and intra-ideological differences emerging from authority-, religion-, closeness-, and conflict-based social roles. This suggests these constructs possess strong predictive potential to separate terrorist groups through nuanced expressions observed in their communication behaviour and advances our understanding of how these groups deploy harmful ideology.

VOX-Pol Blog post.

Mainstream risk assessment frameworks such as TRAP-18, ERG22+, VERA-2R, and RADAR largely use Structured Professional Judgement to map individuals against four critical factors; ideology, affiliation, grievance, and moral emotions. However, the growing use of online communication platforms by extremists presents a series of opportunities to complement or extend existing risk assessment frameworks. Here, we examine linguistic markers of morality and emotion in ideologically diverse online discussion groups and discuss their relevance to extant risk assessment frameworks. Specifically, we draw on social media data from the Reddit platform collected across a range of community topics. Nine hundred and eighty-eight threads containing 272,298 individual comments were processed before constructing high-order models of moral emotions. Emotional and moral linguistic content was then derived from these comments. We then conducted comparisons of linguistic content between mainstream left and right political discourse, anti-Muslim (far-right), Men’s Rights (Incel-like), and a nonviolent apolitical control group. Results show that a combination of individualising moral communication and high emotionality separate far-right and Incel-like groups from mainstream political discourse and provide an early warning opportunity.

VOX-Pol Blog post.

VOX-Pol Blog post.

VOX-Pol Blog post.