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This resarch note examines the ways in which Islamic State supporters on Telegram, an encrypted messaging app, renegotiate gender boundaries. The introduction positions receptions of female ISIS accounts in the online space within the context of the roles that women are expected to fill and ISIS’s tentative acceptance of women fighting on the battlefield. An overview of Telegram gender social norms is provided before discussing the methodology used to gather supporting archival data to analyze the renegotiation of gender boundaries on Telegram. This section is followed by an analysis of a case study that considers the wider implications of what this says about women’s agency and involvement in terrorist groups online. The conclusion addresses the policy implications of possible shifts in gender social norms and the shape that women’s engagement in violent jihadist groups might take in the future.

Extremists and terrorists have found the online sphere, and specifically its social networks, to be an efficient tool for advancing their methods and political needs. The legal responses to the resulting threats from this online activity vary from country to country. The immense importance of the Internet in the everyday life of billions of people worldwide has raised difficult questions regarding the attempt to regulate online activity, especially in relation to the right of privacy and freedom of speech. This report examines how western democracies balance, from a legal point of view, the need to protect their populations from terrorist attacks and their duty to preserve the democratic rights of privacy and free speech.

Why do we use the term “toxic narrative”? The concept of “toxic communication” has been established in the English-speaking world since the 1960s. The term has also been borrowed in Germany to refer to linguistic behavior that has a negative influence on its environment. When we speak of toxic narratives, we are referring to accounts of the world that supply the pertinent “events” and interpretations for such communication.

It is necessary to process such narratives – decoding them, examining their core content and classifying them – in order to respond to them cogently and successfully. The present report is intended to make a contribution to this effort.

The purpose of this paper is to explore the use of community question answering sites (CQAs) on the topic of terrorism. Three research questions are investigated: what are the dominant themes reflected in terrorism-related questions? How do answer characteristics vary with question themes? How does users’ anonymity relate to question themes and answer characteristics?

Data include 300 questions that attracted 2,194 answers on the community question answering Yahoo! Answers. Content analysis was employed.

The questions reflected the community’s information needs ranging from the life of extremists to counter-terrorism policies. Answers were laden with negative emotions reflecting hate speech and Islamophobia, making claims that were rarely verifiable. Users who posted sensitive content generally remained anonymous.

This paper raises awareness of how CQAs are used to exchange information about sensitive topics such as terrorism. It calls for governments and law enforcement agencies to collaborate with major social media companies to develop a process for cross-platform blacklisting of users and content, as well as identifying those who are vulnerable.

Theoretically, it contributes to the academic discourse on terrorism in CQAs by exploring the type of questions asked, and the sort of answers they attract. Methodologically, the paper serves to enrich the literature around terrorism and social media that has hitherto mostly drawn data from Facebook and Twitter.

Islamophobic hate speech on social media is a growing concern in contemporary Western politics and society. It can inflict considerable harm on any victims who are targeted, create a sense of fear and exclusion amongst their communities, toxify public discourse and motivate other forms of extremist and hateful behavior. Accordingly, there is a pressing need for automated tools to detect and classify Islamophobic hate speech robustly and at scale, thereby enabling quantitative analyses of large textual datasets, such as those collected from social media. Previous research has mostly approached the automated detection of hate speech as a binary task. However, the varied nature of Islamophobia means that this is often inappropriate for both theoretically informed social science and effective monitoring of social media platforms. Drawing on in-depth conceptual work we build an automated software tool which distinguishes between non-Islamophobic, weak Islamophobic and strong Islamophobic content. Accuracy is 77.6% and balanced accuracy is 83%. Our tool enables future quantitative research into the drivers, spread, prevalence and effects of Islamophobic hate speech on social media.

As recent perpetrators of racially-motivated mass-shootings were visitors and contributors to online white supremacist networks, this article presents a preliminary model that attempts to understand the social psychological effects of interacting in these networks. Combining Jonathan Turner’s theory of the social psychological roots of extreme violence, scholarship on the white supremacist movement, and research on computer-mediated communication, it suggests that interactions in online white supremacist networks accelerate the conversion from secondary to tertiary deviance, amplify the negative emotional energy released by this conversion, and, under certain conditions, transform this energy into a violent kinetic force. The model is not unique to online white supremacist networks and will hopefully guide research in other types of networks as well.