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In the space of 36 minutes on March 15, 2019, it is alleged that Brenton Tarrant, an Australian far-right extremist, fatally shot 51 people in two mosques in Christchurch in the deadliest terrorist attack in New Zealand’s history. What was unique about Tarrant’s attack—at least insofar as extreme-right terrorism is concerned—is that he livestreamed his atrocity on Facebook and in doing so, highlighted the Achilles heel of such platforms when faced with the viral dissemination of extremely violent content.

The rise of the alt-right as a potent and sometimes violent political force has been well documented. Yet the journey of an individual towards upholding these ideologies is less well understood. Alt-righters are not instantly converted, but rather incrementally nudged along a particular medial pathway. Drawing on video testimonies, chat logs, and other studies, this paper explores the interaction between this alt-right “pipeline” and the psyche of a user. It suggests three overlapping cognitive phases that occur within this journey: normalization, acclimation, and dehumanization. Finally, the article examines the individual who has reached the end of this journey, an extremist who nevertheless remains largely unregistered within traditional terrorist classifications.

Countering online hate speech is a critical yet challenging task, but one which can be aided by the use of Natural Language Processing (NLP) techniques. Previous research has primarily focused on the development of NLP methods to automatically and effectively detect online hate speech while disregarding further action needed to calm and discourage individuals from using hate speech in the future. In addition, most existing hate speech datasets treat each post as an isolated instance, ignoring the conversational context. In this paper, we propose a novel task of generative hate speech intervention, where the goal is to automatically generate responses to intervene during online conversations that contain hate speech. As a part of this work, we introduce two fully-labeled large-scale hate speech intervention datasets collected from Gab and Reddit. These datasets provide conversation segments, hate speech labels, as well as intervention responses written by Mechanical Turk Workers. In this paper, we also analyze the datasets to understand the common intervention strategies and explore the performance of common automatic response generation methods on these new datasets to provide a benchmark for future research.

This article maps mechanisms by which online social media activities may contribute to right-wing political violence. High-impact studies on the wave of right-wing and racist violence in the 1990s and early 2000s established that mass media discourse on immigrants and previous violent incidents had a significant influence on the prevalence of radical right violence. This link was captured by Koopmans’s and Olzak’s notion of discursive opportunities. However, this was before the dominance of online social networks and social media, which changed the media landscape radically. We argue for broadening and refining the operationalization of the concept of discursive opportunities in social movement studies as well as including in our theoretical models new mechanisms brought about by the new online media. In relation to radical right and anti-immigrant mobilizations in Sweden in the 2010s, we elaborate and exemplify three mechanisms through which activities on social media may affect the incidence of violence: a) having an increasingly co-produced discursive opportunity structure, b) making inter-group dynamics in movement groups and networks trans-local, and c) sharing (rare) practical information and co-ordinating activities.

Despite the visible presence of violent extremist groups, and evidence of their connection with transnational groups such as Islamic State and Al-Qaeda, the number of empirical studies on this topic is limited in Bangladesh. There have been over 50 violent extremist attacks in Bangladesh in recent years (2013-2017) and digital media was used in different ways in most of these attacks. There appear to be no scholarly articles addressing this phenomenon in Bangladesh. To fill this gap, this project sheds light on the subject by analyzing life stories of Bangladeshi violent extremists. The data for this project was collected from content analysis of newspaper reports, Jihadi online magazines, and videos. Besides presenting current trends on how extremists are using digital media, this paper identifies challenges for counter-terrorism efforts in Bangladesh and provides suggestions to mitigate these challenges.

Both right-wing extremists and Islamist groups use social media to spread their political and ideological messages. To prevent extremist groups from abusing new media ecosystems and their mechanisms for their purposes, preventative measures must be based on sound knowledge of their methods. In this article Daniel Köhler and Julia Ebner explain which media strategies rightwing extremist and Islamist groups pursue in order to target internet users who are susceptible to radicalisation, recruit them for their purposes, intimidate political opponents and manipulate online discussion. Despite the different ideological
convictions of the groups, their methods overlap.