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In this paper we use methods of social network analysis to examine the inter-organizational structure of the white supremacist movement. Treating links between Internet websites as ties of affinity, communication, or potential coordination, we investigate the structural properties of connections among white supremacist groups. White supremacism appears to be a relatively decentralized movement with multiple centers of influence, but without sharp cleavages between factions. Interorganizational links are stronger among groups with a special interest in mutual affirmation of their intellectual legitimacy (Holocaust revisionists) or cultural identity (racist skinheads) and weaker among groups that compete for members (political parties) or customers (commercial enterprises). The network is relatively isolated from both mainstream conservatives and other extremist groups. Christian Identity theology appears ineffective as a unifying creed of the movement, while Nazi sympathies are pervasive. Recruitment is facilitated by links between youth and adult organizations and by the propaganda efforts of more covertly racist groups. Links connect groups in many countries, suggesting the potential of the Internet to facilitate a whitesupremacist “cyber-community” that transcends regional and national boundaries.

The Internet and, in particular, Online Social Networks have changed the way that terrorist and extremist groups can influence and radicalise individuals. Recent reports show that the mode of operation of these groups starts by exposing a wide audience to extremist material online, before migrating them to less open online platforms for further radicalization. Thus, identifying radical content online is crucial to limit the reach and spread of the extremist narrative. In this paper, our aim is to identify measures to automatically detect radical content in social media. We identify several signals, including textual, psychological and behavioural, that together allow for the classification of radical messages. Our contribution is threefold: (1) we analyze propaganda material published by extremist groups and create a contextual text-based model of radical content, (2) we build a model of psychological properties inferred from these material, and (3) we evaluate these models on Twitter to determine the extent to which it is possible to automatically identify online radical tweets. Our results show that radical users do exhibit distinguishable textual, psychological, and behavioural properties. We find that the psychological properties are among the most distinguishing features. Additionally, our results show that textual models using vector embedding features significantly improves the detection over TF-IDF features. We validate our approach on two experiments achieving high accuracy. Our findings can be utilized as signals for detecting online radicalization activities.

The project Mapping Networks and Narratives of Online Right-Wing Extremists in New South Wales (NSW) used the systematic mining and analysis of online data to generate evidence-based insights into online right-wing extremism (RWE) across the state. The project was conducted between July 2019 and February 2020 with data collection occurring from August to November 2019. The project addressed three key areas:

– What is the nature of the online RWE environment in NSW?
– How are themes and narratives framed in different online contexts in order to mobilise support?
– What level of risk does the online RWE environment pose?

The research areas were framed as broad questions to facilitate wide exploratory research into the online RWE movement in NSW, a milieu that has been little studied. This breadth of scope was considered pertinent in the wake of the March 2019 mass casualty terrorist attack in Christchurch, New Zealand, by an attacker originating from NSW.

Despite an increasing number of attacks by violent anti-Good Friday Agreement (GFA) Republicans from 2009 there is still relatively little understanding of the nature of these organizations or the likely longevity of their campaign(s). This analysis argues that the current upsurge of violence is likely to continue for the foreseeable future, due to a combination of factors that entrench republican ideology. The fractured nature of anti-GFA groups and the declining stature of the Provisional movement are key factors that energize anti-agreement sentiment. In particular, this study identifies the Internet as one of the most significant emerging drivers in that it has the potential to sustain social networks that create and reinforce a traditional minded Irish Republican constituency implacably committed to using violence in pursuit of its goals.

One of the paradoxical effects of the 7 July bombings in London was to expose the ambivalence in the British government’s attempt to wage war on terror by forcefully prosecuting war against those who resort to jihad abroad, actively participating in coalitions of the willing whether in Afghanistan or Iraq, while affording some of Islamism’s key ideologists and strategists a high degree of latitude in the United Kingdom itself. This indicates a number of contradictions in official policy that simultaneously recognizes the globalized threat from violent Islamic militancy while, under the rubric of multiculturalism, tolerating those very strains of Islamist radicalism, some of which draw upon the interdependent and transnational character of conflict, to render the UK vulnerable to those very same violent forces. Consequently, the British authorities displayed a studied indifference towards this developing transnational phenomenon both during the 1990s and in some respects even after the London bombings. To explore the curious character of the government’s response to the Islamist threat requires the examination of the emergence of this radical ideological understanding and what it entails as a reaction to modernization and secularism in both thought and practice. The analysis explores how government policies often facilitated the non-negotiable identity politics of those promoting a pure, authentic and regenerated Islamic order both in the UK and abroad. This reflected a profound misunderstanding of the growing source and appeal of radical Islam that can be interpreted as a consequence of the slow-motion collision between modernity in its recent globalized form and an Islamic social character, which renders standard western modernization theory, and indeed, the notion of a ‘social science’ itself, deeply questionable.

This paper explores various Social Network Analysis (SNA) techniques in order to identify a range of potentially ‘important’ members of Islamic Networks within Dark Web Forums. For this experiment, we conducted our investigation on five forums collected in previous work as part of the DarkWeb Forum portal and built upon the tool support created in our previous research in order to visualise and analyse the network. Whilst existing work attempts to identify these structures through state-of-the-art Computational Linguistic techniques, our work relies on the communication metadata alone. Our analysis involved first calculating a range of SNA metrics to better understand the group members, and then apply unsupervised learning in order to create clusters that would help classify the Dark Web Forums users into hierarchical clusters. In order to create our social networks, we investigated the effect of repeated author resolution and various weighting schemes on the ranking of forum members by creating four social networks per forum and evaluating the correlation of the top n users (for n = 10; 20; 30; 40; 50 and 100). Our results identified that varying the weighting schemes created more consistent ranking schemes than varying the repeated author resolution.