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VOX-Pol Blog Post.

VOX-Pol Blog post.

Radical, terroristic organizations pose threats to business, government, and society. The ubiquity of the modern Web and its participatory architecture have enabled such groups to become full-blown online propaganda machines. Today, radicalization that eventually leads to acts of terror occurs predominantly on the Web. Radical ideologies can be spread, in many cases unchecked, by malicious actors who take advantage of the frequently lax surveillance apparatus of online social platforms. This paper argues that an overlooked, essential first step to interdicting this threat is the large-scale, structured collection of knowledge regarding these ideologies in open machine-readable formats. Using Collective Action Framing Theory, this study develops a trio of design artifacts: the Terror Beliefs Ontology (TBO) for a general ontology of terroristic ideology, the Frame Discovery System (FDS) to automatically populate this ontology, and the Frame Resonance Detection System (FRDS) to accurately identify online personae or postings that espouse a radical ideology known to TBO. With a comprehensive evaluation, we demonstrate how these three instantiated design artifacts, working in concert, can automatically construct a knowledge representation of heterogeneous terroristic ideologies and accurately detect radical online postings. We offer the first design that can assign Web text to any radical ideology without the use of a hand-labeled training corpus.

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

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.