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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.

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.

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.

This report offers a preliminary analysis of the effectiveness of network disruptions in achieving one specific outcome: tackling terrorist violence. It analyses the relationship between network disruptions and deaths and injuries from terrorist attacks to determine whether there is support for the commonly made argument that network disruptions are an important counterterrorism tactic. Using a panel dataset of daily incidents of national-level network disruptions and terrorist attacks globally between 2016 and 2019, a fixed effects regression model shows that national-level network disruptions are not correlated with the number of people killed or injured in terrorist attacks. In addition, there is no correlation between a ban on social media platforms – specifically Facebook, Twitter and WhatsApp – and deaths or injuries from terrorist violence. This analysis has some limitations that make it difficult to make a causal claim, such as the non-random assignment of the treatment (that is, network disruptions) and the absence of a control variable to capture increased security around network disruptions. In general, these findings offer another perspective on the debate on network shutdowns, which often centres on the implications of shutdowns for human rights and democratic engagement and does not typically delve into empirical evidence on what network shutdowns can or cannot accomplish.

This project examines the uses of social media for policing domestic extremism and
disorder in the UK. The collection and analysis of social media data for the purposes
of policing forms part of a broader shift from ‘reactive’ to ‘proactive’ forms of
governance in which state bodies engage in big data analysis to predict, preempt and
respond in real time to a range of social problems. However, there is a lack of
research that accounts for the ways in which different state bodies are making use of
big data, and how big data is changing the way states research, prioritize and act in
relation to social and political issues.