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The paper describes a recently-created Twitter corpus of about 6,000 tweets, annotated for hate speech against immigrants, and developed to be a reference dataset for an automatic system of hate speech monitoring. The annotation scheme was therefore specifically designed to account for the multiplicity of factors that can contribute to the definition of a hate speech notion, and to offer a broader tagset capable of better representing all those factors, which may increase, or rather mitigate, the impact of the message. This resulted in a scheme that includes, besides hate speech, the following categories: aggressiveness, offensiveness, irony, stereotype, and (on an experimental basis) intensity. The paper hereby presented namely focuses on how this annotation scheme was designed and applied to the corpus. In particular, also comparing the annotation produced by CrowdFlower contributors and by expert annotators, we make some remarks about the value of the novel resource as gold standard, which stems from a preliminary qualitative analysis of the annotated data and on future corpus development.

The Counter Terrorism and Security Act (2015) introduced a binding duty on public sector bodies in the United Kingdom (UK), including education, to have ‘due regard to the need to prevent people from being drawn into terrorism’. The Prevent duty has become widely controversial in the Higher Education (HE) sector with questions as to whether it contravenes academic freedom and freedom of speech.
This research seeks to identify how Prevent may be applied to cyberspace to reduce risk of students being radicalised online at universities. Through semi-structured interviews (N= 16) with individuals working in Prevent and HE, attention is given to the capability of monitoring and filtering website content, which must be considered by universities as part of Prevent compliance. In addition, non-technical methods of reducing radicalisation in cyberspace are explored. Consideration is given to building students’ resilience to challenging information they see online through developing counter-narrative content for social media platforms. With students developing counter-narrative content themselves, specifically addressing vulnerability drivers to radicalisation, universities can enhance compliance with Prevent and create counter extremist content which can be used in cyberspace both in and outside of HE.

This paper introduces the concept of “imagined extremist communities,” a term that encapsulates the unique social landscape where right-wing lone actors, despite not being affiliated with organised groups, partake in a form of communal interaction. By examining the cases of Anders Behring Breivik, Brenton Harrison Tarrant, and Philip Manshaus, this paper illuminates how group-based and lone actors are more alike than what is conventionally expressed in existing research. Although lone actors are not subject to an external command like group-based actors are, the imagined extremist community functions as a “group” for lone actors and is, for all practical purposes, a corresponding alternative to a terror cell. During the radicalisation process, these individuals seek and turn to the imagined extremist community, enabling them to form a sense of belonging and identification and underscoring that these actors, although conventionally labelled as “lone,” are immersed in an alternative culture that nurtures their ideas and sustains their extremist ideology. This becomes particularly evident through their cognitive radicalisation, a process amplified by their psychological predispositions. The concept of the imagined extremist community elucidates how lone actors, especially those embracing right-wing ideologies, are subject to radical influences. Their conservative traits and psychological dispositions make them particularly receptive to the appeal of such communities.

The counterterrorism and CVE community has long questioned the effectiveness of counterspeech in countering extremism online. While most evaluation of counterspeech rely on limited reach and engagement metrics, this paper explores two models to better measure behavioral change and sentiment analysis. Conducted via partnerships between Facebook and counter-extremism NGOs, the first model uses A/B testing to analyze the effects of counterspeech exposure on low-prevalence-high-risk audiences engaging with Islamist extremist terrorist content. The second model builds upon online safety intervention approaches and the Redirect Method through a search based “get-help” module, redirecting white-supremacy and Neo-Nazi related search-terms to disengagement NGOs.

The counterterrorism and CVE community has long questioned the effectiveness of counterspeech in countering extremism online. While most evaluation of counterspeech rely on limited reach and engagement metrics, this paper explores two models to better measure behavioral change and sentiment analysis. Conducted via partnerships between Facebook and counter-extremism NGOs, the first model uses A/B testing to analyze the effects of counterspeech exposure on low-prevalence-high-risk audiences engaging with Islamist extremist terrorist content. The second model builds upon online safety intervention approaches and the Redirect Method
through a search based “get-help” module, redirecting whitesupremacy and Neo-Nazi related search-terms to disengagement NGOs.

Approaches for strategically countering or providing alternatives to hate speech and extremism online have evolved substantively in the last ten years. Technological advancement and a generation of young activists who have been socialized as digital natives have facilitated a maelstrom of both hate-based extremist content and attempts to counter this material in different guises and through diverse channels. The rate and pace of change within the tech sector, and social media growth in particular, have meant that although counterspeech is now more prevalent than ever before, it requires greater guidance and more robust public–private partnerships to effectively prevent and counter extremism online. The chapter embraces a cross-platform and international overview of some of the best practices within efforts to prevent and counter violent extremism online and discusses the future of counterspeech with recommendations for expanded innovation and partnership models.