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The global war on terror (“GWOT”) is being fought on many levels. In addition to traditional terror and counterterror activity, both sides are engaged in a public relations and propaganda war, employing the media, willingly and unwillingly, to support their positions. Hovering over these war campaigns are information technologies, which include the Internet. This article provides an introduction to various online content concealing practices that have been employed by those seeking to conceal or limit access to information on the Internet, including terrorist organizations. Further, there is a discussion on tracking and monitoring of website visitors. After reviewing open source information and websites, this article examines techniques and technologies that are easily available to terrorist organizations — foreign and domestic — whose structure can be obtained through Internet websites. The article then turns to a discussion of the legal issues posed by active and passive website monitoring techniques.

Hate groups are increasingly using multiple social media platforms to promote extremist ideologies. Yet we know little about their communication practices across platforms. How do hate groups (or “in-groups”), frame their hateful agenda against the targeted group or the “out-group?” How do they share information? Utilizing “framing” theory from social movement research and analyzing domains in the shared links, we juxtapose the Facebook and Twitter communication of 72 Southern Poverty Law Center (SPLC) designated hate groups spanning five hate ideologies. Our findings show that hate groups use Twitter for educating the audience about problems with the out-group, maintaining positive self-image by emphasizing in-group’s high social status, and for demanding policy changes to negatively affect the out-group. On Facebook, they use fear appeals, call for active participation in group events (membership requests), all while portraying themselves as being oppressed by the out-group and failed by the system. Our study unravels the ecosystem of cross-platform communication by hate groups, suggesting that they use Facebook for group radicalization and recruitment, while Twitter for reaching a diverse follower base.

Crafted as an open communication platform characterized by high anonymity and minimal moderation, Telegram has garnered increasing popularity among activists operating within repressive political contexts, as well as among political extremists and conspiracy theorists. While Telegram offers valuable data access to research non-institutionalized activism, scholars studying the latter on Telegram face unique theoretical and methodological challenges in systematically defining, selecting, sampling, and classifying relevant actors and content. This literature review addresses these issues by considering a wide range of recent research. In particular, it discusses the methodological challenges of sampling and classifying heterogeneous groups of (often non-institutionalized) actors. Drawing on social movement research, we first identify challenges specific to the characteristics of non-institutionalized actors and how they become interlaced with Telegram’s platform infrastructure and requirements. We then discuss strategies from previous Telegram research for the identification and sampling of a study population through multistage sampling procedures and the classification of actors. Finally, we derive challenges and potential strategies for future research and discuss ethical challenges.

In recent decades, political parties espousing extreme nationalist, xenophobic, and even outright racist platforms have enjoyed variable success in national elections across Europe. While vibrant research literature has sought to better understand the sources of support for such parties, remarkably little attention has been paid to the interplay between parties and the broader social networks of extremism in which they are embedded. To remedy this deficiency, the present study examines the relations between far-right parliamentary parties and their extra-parliamentary networks. One level of analysis tests whether there is a relationship between a party’s position within a network and its sustainability. Social network analysis is employed to assess the nature and structure of ties between Belgian organizations online. In addition, systematic textual analysis of website content is used to determine how a party ideological position within the network impacts its sustainability. The second level of analysis is a qualitative study based on in-depth interviews with members of the Flemish nationalist organization in order to better understand how actors experience social networks. Evidence suggests that the most sustainable parties are those that have dense connections with other nationalist organizations. Mapping relations between far-right parties that compete openly within the rules of institutionalized democracy and their wider social networks can provide important policy-relevant insight into contemporary challenges posed by illiberal forces.

In the domain of computer science, the last years have witnessed the improvement of social network analysis at scale. One of the most challenging aspects of social network analysis is community detection; analysts use a variety of tools to visualise the spontaneous group structure emerging from interactions and friendship relations in multi-million-user networks. This visualisation, combined with influencer detection and automated text analysis tools such as topic detection, enables the analyst to grasp most of the complexity of a social network. This computer-science-oriented study explores three lines of research concerning online extremism. First, about the emerging narratives and the topics that can be found on open platforms. We show that many actors actively use terror-group related terms; most cannot be directly tied to any specific organisation. A second axis concerns the connections between platforms: the information space has no central point as content is shared across platforms. However, the links reveal clusters of locations: we observe a group of Pakistan-India conflict mentions, and a cluster of US alt-right websites, transforming terrorism into a migration problem. The third axis relates to the social media landscape structure. We rely on a combination of document-level topic modelling and graph analysis to detect and explore the social data, visualising the types of groups that are active on the topic. Among the results, we found a small botnet circulating a pro-Daesh pamphlet and a set of grassroot reactions that managed to moderate a controversial pro-Jihadi post on Reddit.

This study explores the internal dynamics and networks of terrorist groups in cyberspace—in particular, Al-Qaeda and the Islamic State of Iraq and al-Sham (ISIS). Using a “Global Cyberterrorism Dataset” that features data on cyberterror attacks between 2011 and 2016, this research analyzes these two terrorist groups through the lens of a cyber-conflict theory that integrates conflict theory with Jaishankar’s space transition theory. Through a network analysis methodology, we examine the invisible relationships and connections between the national origins and target countries of cyberterror attacks. The analysis focuses on the networks of national origins of terrorists and victims, network structures of Al-Qaeda and ISIS actors, and clustering networks of Al-Qaeda and ISIS cyberterrorists. Results indicate that terror in cyberspace is ubiquitous, more flexible than traditional terrorism, and that cyberattacks mostly occurred within the countries of origin. We conclude by discussing the complex features of cyberterror networks and identify some of the geostrategic implications of the divergent cyber strategies adopted by Al-Qaeda and ISIS.