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The publication of online manifestos has become a common element associated with far-right terrorist violence in the West. Perpetrators of extremist attacks produce and circulate written materials for inspiration, tactical instruction, and notoriety. This presents policymakers and media organizations with considerable analytical challenges. Each far-right text represents a constituent element within a growing body of extremist literature stewarded by a digitally interconnected community; situating texts in this way yields intriguing findings. This article examines the reception and circulation of four written texts, both printed and online, by the violent far-right: (1) William Luther Pierce’s The Turner Diaries, (2) written works attributed to the White Wolves in Britain during the 1990s, (3) Anders Behring Breivik’s 2011 manifesto, and (4) Christchurch attacker Brenton Tarrant’s 2019 livestream and online manifesto.

The article explores the patterning and functioning of attitude semantics in the practice of identity attacks within terrorist communications. Positioned in facework and stance-taking research (e.g. Tracy & Tracy, 1998, 2008, 2017), it introduces the concepts of ‘evaluative textbites’ and ‘attitudinal priming’ to linguistic examinations, advocating a functional approach to unravelling identity attacks, drawing on corpus analysis methods (e.g. word frequency, and concordance-line qualitative analysis) and the Appraisal framework (Martin & White, 2005). Findings reveal that, linked with stance-taking activity, attitudinal priming offers insights into how specific ideational targets are primed for particular attitudinal, evaluative functions. Evaluative textbites provide linguistic evidence of an author’s encoded hostile attitude and the nuanced patterning and functioning of ‘ideation-attitude’ co-occurrences in these attacks. Identity attacks are a rhetorical tool, normative and valuation-based, targeting individuals’ or out-groups’ immoral behaviours and devaluing victims by reference to their personal traits, power-distance relationships, interactional roles, and master identities. This article offers implications for future study of identity attacks in hate crimes, genocidal rhetoric, and defamation texts, and strengthens counter-extremism efforts by illuminating the investigative value of identity work.

Unlike one-to-one threats, terrorist threat texts constitute a form of violence and a language crime that is committed in a complex context of public intimidation, and are communicated publicly and designed strategically to force desired sociopolitical changes . Contributing to law enforcement and threat assessors’ fuller understanding of the discursive nature of threat texts in terrorism context, this paper examines how language is used dialogically to communicate threats and to construct both the purpose of threatened actions and the victims. The paper uses a critical discourse analytic approach and takes a set of eleven digital threat texts made by two jihadists as a case study. It draws on van Dijk’s concept of ideology , the law enforcement-based taxonomy of threat types as reported by Napier and Mardigian , van Leeuwen’s model of social actor representation and discursive construction of purpose of social actions , and Martin and White’s Engagement system . The analysis reveals victims specified and genericised, excluded and adversary. This linguistic construction is underpinned by a dichotomous conceptualisation of the social actors’ affiliations, positions, values, cultural activities, goals, and material and symbolic resources. The threats are delivered to the victims, agents acting on their behalf (e.g. security forces) or property associated with them (e.g. oil refinery), and are of two primary types—direct, and veiled. The former are predominant and serve inter alia to augment the public-intimidation impact of terrorist discourse. Threatened violence is of goal-, means- and/or effect-oriented social purposes, which suggest a categorisation of threats based on these purposes. The analysis reveals a dialectic, refutative nature of argumentation, and a discourse pregnant with heteroglossic utterances that contract (i) to close off and disalign with state officials’ contradictory voices, and (ii) to produce tension, providing clues to terrorists’ motivations and what constitutes the heart of political violence.

Increasing attention paid to the far right commonly glosses over transnational activity, which reflects an imperial strategy to globalize far-right thinking and its attendant discursive and physical violence against others. Empirically, I focus on far-right transnational linkages among ordinary people (not state officials) between the United States and Europe and across Europe, and between India and the Indian diaspora especially in the United States to present variation in organizational strategies. Transnational far-right activity’s under-the-radar status is due to dated assumptions that presume transnational linkages occur on a top, down basis, and emanate from the formal political sphere, overlooking significant transnational material and immaterial linkages forged online by ordinary people who carry messaging through the far-right online ecosystem to affect political decision-making and societal discourses more generally. In the case of the far-right Indian diaspora, public-facing self-presentation aligns with Hinduism, which embraces peace and coexistence, despite the pursuit of the opposite, and this multicultural guise complements the bottom, up flow of far-right messaging to render Hindu nationalism, Hindutva, difficult to see. The far right throughout the world unites around casteism, the embrace of a fixed and “natural” societal hierarchy, and is fueled emotionally by the Great Replacement conspiracy theory. Both casteism and replacement theory are adaptable to different contexts to enable unity across contexts despite internal diversity among far-right groups, notably in the United States, and diverse targets of hatred. Far-right unity-in-diversity obviates constraints on transnational activity based on nativism and enables different in organization and psychosocial and cultural practices.

The ever-increasing use of the internet by terrorist groups as a platform for the dissemination of radical, violent ideologies is well documented. The internet has, in this way, become a breeding ground for potential lone-wolf terrorists; that is, individuals who commit acts of terror inspired by the ideological rhetoric emitted by terrorist organizations. These individuals are characterized by their lack of formal affiliation with terror organizations, making them difficult to intercept with traditional intelligence techniques. The radicalization of individuals on the internet poses a considerable threat to law enforcement and national security officials. This new medium of radicalization, however, also presents new opportunities for the interdiction of lone wolf terrorism. This dissertation is an account of the development and evaluation of an information technology (IT) framework for detecting potentially radicalized individuals on social media sites and Web fora. Unifying Collective Action Framing Theory (CAFT) and a radicalization model of lone wolf terrorism, this dissertation analyzes a corpus of propaganda documents produced by V several, radically different, terror organizations. This analysis provides the building blocks to define a knowledge model of terrorist ideological framing that is implemented as a Semantic Web Ontology. Using several techniques for ontology guided information extraction, the resultant ontology can be accurately processed from textual data sources. This dissertation subsequently defines several techniques that leverage the populated ontological representation for automatically identifying individuals who are potentially radicalized to one or more terrorist ideologies based on their postings on social media and other Web fora. The dissertation also discusses how the ontology can be queried using intuitive structured query languages to infer triggering events in the news. The prototype system is evaluated in the context of classification and is shown to provide state of the art results. The main outputs of this research are (1) an ontological model of terrorist ideologies (2) an information extraction framework capable of identifying and extracting terrorist ideologies from text, (3) a classification methodology for classifying Web content as resonating the ideology of one or more terrorist groups and (4) a methodology for rapidly identifying news content of relevance to one or more terrorist groups

The ever-increasing use of the internet by terrorist groups as a platform for the dissemination of radical, violent ideologies is well documented. The internet has, in this way, become a breeding ground for potential lone-wolf terrorists; that is, individuals who commit acts of terror inspired by the ideological rhetoric emitted by terrorist organizations. These individuals are characterized by their lack of formal affiliation with terror organizations, making them difficult to intercept with traditional intelligence techniques. The radicalization of individuals on the internet poses a considerable threat to law enforcement and national security officials. This new medium of radicalization, however, also presents new opportunities for the interdiction of lone-wolf terrorism. This dissertation is an account of the development and evaluation of an information technology (IT) framework for detecting potentially radicalized individuals on social media sites and Web fora. Unifying Collective Action Framing Theory (CAFT) and a radicalization model of lone-wolf terrorism, this dissertation analyzes a corpus of propaganda documents produced by several, radically different, terror organizations. This analysis provides the building blocks to define a knowledge model of terrorist ideological framing that is implemented as a Semantic Web Ontology. Using several techniques for ontology guided information extraction, the resultant ontology can be accurately processed from textual data sources. This dissertation subsequently defines several techniques that leverage the populated ontological representation for automatically identifying individuals who are potentially radicalized to one or more terrorist ideologies based on their postings on social media and other Web fora. The dissertation also discusses how the ontology can be queried using intuitive structured query languages to infer triggering events in the news. The prototype system is evaluated in the context of classification and is shown to provide state of the art results. The main outputs of this research are (1) an ontological model of terrorist ideologies (2) an information extraction framework capable of identifying and extracting terrorist ideologies from text, (3) a classification methodology for classifying Web content as resonating the ideology of one or more terrorist groups and (4) a methodology for rapidly identifying news content of relevance to one or more terrorist groups.