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This study is a content analysis of Islamic State of Iraq and Syria (ISIS)’s French-language magazine Dar al-Islam. The first seven issues of the magazine are quantitatively examined and broken down into the number of articles, images, and terms used as a means of determining how ISIS targets French-speaking individuals. This study find that ISIS focuses on religious terminology and justifications to rationalize its existence and its fight. Also, despite being a French-language magazine, a majority of the focus is on Middle Eastern groups, not Western groups. Overall, the magazine is similar, but not a carbon copy to ISIS’s English-language magazine, Dabiq.

This paper maps communication channels exploited by the Salafi-jihadist violent extremist organisations (VEOs) and their followers between March 2020 and June 2022 on The Onion Router (TOR). It argues that the true scale of digital jihadist presence on TOR has remained insignificant for years. Militant Islamists have mostly used .onion domains as backup propaganda dissemination channels, which enable content takedown policies introduced by countering violent extremism stakeholders to be circumvented. Aside from propaganda distribution, TOR attracts Salafi-jihadist VEOs and their followers for other reasons, as it facilitates anonymous communication, crowdfunding, sharing of terrorist manuals or the organisation of terrorist attacks.

VOX-Pol Blog post.

Terrorism research has begun to focus on the issue of radicalization, or the acceptance of ideological belief systems that lead toward violence. There has been particular attention paid to the role of the Internet in the exposure to and promotion of radical ideas. There is, however, minimal work that attempts to model the ways that messages are spread or how individual participation in radical on-line communities operates. In this paper, we present a stochastic linear system to represent the evolution of contribution to a sample of 126 threads in an on-line forum where individuals discuss radical belief systems. To estimate or predict the time-varying contributions of agents for given onlineforum data, each agent’s contribution has been modeled as a state variable. We then use the expectation-maximization (EM) algorithm to identify the model parameters including the adjacency matrix of the graph constructed among participating agents along with measurement and system uncertainty levels in online-postings. Our approach reveals the identified dynamical influences among agents in the time-varying shaping of the contribution in a datadriven fashion. We use the real-world data from online-postings to demonstrate the usefulness of our approach, and its application toward on-line radicalization.

VOX-Pol Blog post.

VOX-Pol Blog post.