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This paper combines corpus linguistics and critical discourse analysis methodologies in order to investigate the discourses and cyber activism of the British right-wing nationalist party, Britain First. A study of a corpus of texts produced by elite members of the group reveals a racist, xenophobic stance which constructs Islam and Muslims as the radical, dangerous ‘Other’. This creates a discourse of fear that threatens the way of life of the indigenous in-group of the British people. An investigation of the cyber activity of the group demonstrates that Britain First is able to achieve a significant amount of following on social media by publishing populist material that veils their true nature or ideological stance.

The permanent transition to online activity has brought with it a surge in hate speech discourse. This has prompted increased calls for automatic detection methods, most of which currently rely on a dictionary of hate speech words, and supervised classification. This approach often falls short when dealing with newer words and phrases produced by online extremist communities. These code words are used with the aim of evading automatic detection by systems. Code words are frequently used and have benign meanings in regular discourse, for instance, “skypes, googles, bing, yahoos” are all examples of words that have a hidden hate speech meaning. Such overlap presents a challenge to the traditional keyword approach of collecting data that is specific to hate speech. In this work, we first introduced a word embedding model that learns the hidden hate speech meaning of words. With this insight on code words, we developed a classifier that leverages linguistic patterns to reduce the impact of individual words. The proposed method was evaluated across three different datasets to test its generalizability. The empirical results show that the linguistic patterns approach outperforms the baselines and enables further analysis on hate speech expressions.

Without measures of the lethality of terrorist networks, it is very difficult to assess if capturing or killing a terrorist is effective. We present the predictive lethality analysis of terrorist organization () algorithm, which merges machine learning with techniques from graph theory and social network analysis to predict the number of attacks that a terrorist network will carry out based on a network structure alone. We show that is highly accurate on two novel datasets, which cover Al Qaeda (AQ) and the Islamic State (ISIS). Using both machine learning and statistical methods, we show that the most significant macrofeatures for predicting AQ’s lethality are related to their public communications (PCs) and logistical subnetworks, while the leadership and operational subnetworks are most impactful for predicting ISISs lethality. Across both groups, the average degree and the diameters of the strongly connected components (SCCs) within these networks are strongly linked with lethality.

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This literature review seeks to reorient the discourse on radicalization to consider the connection between communication technology and violent extremism. By interrogating three central questions vexing policy-makers, law enforcement officials and academics, this review moves away from a monolithic understanding of the internet and showcases the opportunities afforded by different communications technologies within the context of radicalization and recruitment. As this discussion shows, there is a consensus that despite significant exceptions to the rule, the internet alone does not act as a radicalizing agent, but rather serves as a facilitator and catalyst for terrorist organizations and their respective networks. Despite varying analyses produced within the literature, there is agreement that the virtual sphere does not replace the real world in most instances. Above all, a review of the current literature demonstrates that to answer the crucial questions posed in this article, more empirically-based research is required. This article is a revised and updated version of the 2017 VOX-Pol report Research Perspectives on Online Radicalisation: A Literature Review 2006 to 2016.

With the advent of social media, terrorist organisations have seized an unprecedented opportunity to engage wider audiences with their ideologies and actions. This study aims to develop an understanding of this tactic by analysing its use in the 2013 Westgate Mall hostage crisis. During that event, the Twitter account @HSMPress_ provided continuous updates supporting the actions of the terrorist organisation Al- Shabaab. Situating the event within a framework of Jürgen Habermas’s theories of the Public Sphere and Andrew Mack’s theories of asymmetric warfare, this paper employs Kenneth Burke’s dramatistic pentad to perform a rhetorical analysis of the tweets using both artistic and inartistic factors. It does so in order to understand how they engaged the audience of the terrorist event, emphasising the performative nature of the text in accordance with behaviourist objectives. The results of this analysis will demonstrate how terrorist groups may use platforms like Twitter to achieve a strategic political goal by shifting viewer perspectives, with significant implications for future policy governing social media content and censorship.