Online Library

VOX-Pol Blog Post.

VOX-Pol Blog post.

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.

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 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.

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.