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In July of 2014, a spokesperson for the Islamic State in Iraq and the Levant (ISIL) made a televised announcement that captured the attention of the world – the terrorist organization decided to tweak its name to simply the Islamic State (IS), to indicate its intention of moving beyond Iraq and the Levant and conquering the world. This shift in rhetoric, along with the phenomenon of Muslims and non-Muslims from Western nations leaving their homes, friends, and families behind to join IS, have prompted discussions and debates on what makes this terror group’s message so effective. In the days following IS’s name change, the first issue of its magazine Dabiq was published online through its Al-Hayat Media Center. With versions in English, Arabic, German, French, and more, the magazine gained notoriety for its highproduction value. This study seeks to understand the ideology manifest in IS rhetoric in Dabiq, which makes it so captivating to both sympathizers and agitators alike. This study is an ideological criticism of six of the fifteen issues of Dabiq published; the six issues chosen were all released in relation to catalytic events perpetrated or claimed by the terror group. For instance, the November 2015 Paris attacks or the shooting in San Bernardino, CA, by a ‘radicalized’ couple who pledged allegiance to IS. This study unearthed major themes of political claims, religious appeals, and terrorist actions which IS uses to incite recruitment. This analysis identifies IS’s ideology as one of Political Islamist Terrorism, and concludes with implications concerning exceptionalism and the persuasive appeal of Dabiq.

Why do ordinary people become supportive of violent, extremist ideologies? Over the past several years, tens of thousands of individuals across the world have become attracted to propaganda disseminated by the Islamic State (ISIS), and many have left their home countries to join the organization. This dissertation closely examines possible explanations for pro-ISIS radicalization in Europe and the United States. I argue that anti-Muslim hostility is an important driver of pro-ISIS radicalization, leading individuals who feel isolated to become attracted to the organization’s propaganda. I also contend that groups like ISIS are aware of this pattern, and thus seek to purposefully provoke hostility against potential supporters by carrying out terrorist attacks. I maintain that efforts to stop radicalization should focus on ways to reduce hostility and increase the inclusion of minorities in the West. The various dissertation papers empirically examine different aspects of these arguments. In the first paper, I examine whether anti-Muslim hostility might be driving pro-ISIS radicalization in Europe, by analyzing the online activity of thousands of ISIS sympathizers in France, Germany, Belgium, and the United Kingdom. Matching online radicalization indicators with offline data on vote share for far-right, anti-Muslim parties, I show that the intensity of anti-Muslim hostility at the local (neighborhood/municipality) level strongly correlates with support for ISIS on Twitter. In addition, I show that events that stir anti-Muslim sentiments, such as terrorist attacks and anti-Muslim protests, lead ISIS sympathizers to significantly increase pro-ISIS rhetoric, especially in areas with high far-right support. In the second paper, I argue that armed groups strategically use terrorism to manipulate levels of anti-Muslim hostility in Western countries. I test whether terrorism leads to greater expressions of anti-Muslim hostility using data on thirty-six terrorist attacks perpetrated by radical jihadists in the West from 2010 to 2016, examining how they shaped anti-Muslim attitudes among individuals in targeted countries. I find that individuals systematically and significantly increase the posting of anti-Muslim content on social media after exposure to terrorism. The effect spikes immediately after attacks, decays over time, but remains significantly higher than pre-attack levels up to a month after the events. The results also reveal that the impact of terrorist attacks on anti-Muslim rhetoric is similar for individuals who already expressed hostility to Muslims before the attacks and those who did not. Finally, I observe that the impact of terrorist attacks on anti-Muslim hostility increases with attacks resulting in greater numbers of casualties.  In the third paper, I examine what might be done to stop online radicalization and support for ISIS in the West. I collected data on community engagement events performed in the United States by the Obama Administration, which aimed to increase trust and relationships between the Muslim population and the American government, and combined them with high-frequency, geo-located panel data on tens of thousands of individuals in America who follow Islamic State accounts on Twitter. By analyzing over 100 community engagement events in a Difference-in-Differences design, I find that community engagement activities are systematically and significantly associated with a reduction in pro-ISIS rhetoric on Twitter among individuals located in event areas. In addition, the observed negative relationship between community engagement activities and pro-ISIS rhetoric is stronger in areas that held a large number of these events.

This thesis argues that Hamas and the Islamic State, two non-state armed groups located in the Middle East, each carefully calibrate their own war-fighting activities with their communications approaches in order to achieve their respective political objectives. Drawing on scholarship focusing on non-state armed groups and political communication, as well as other secondary sources such as specialist journalism, the thesis critically analyses online communications material distributed by Hamas and the Islamic State through official and affiliated websites, digital publications, YouTube clips, tweets, and other social media platforms. While there is a striking degree of conformity between the sophisticated, comprehensive, and disciplined communications approaches used by these two groups, the thesis argues that key differences during especially intense periods of conflict — specifically, between June and October 2014 — reflect the divergent ways in which Hamas endorses, and the Islamic State disrupts, the prevailing world order as each pursues their own cause. It also notes that much of the recent scholarship highlighting the use of social media by non-state armed groups overestimate the impact of the virtual world on the actions of their followers in particular and attempts to influence the hearts and minds of a global audience more broadly.

Online social networks have become a powerful venue for political activism. In many cases large, insular online communities form that have been shown to be powerful diffusion mechanisms of both misinformation and propaganda. In some cases, these groups users advocate actions or policies that could be construed as extreme along nearly any distribution of opinion and are thus called Online Extremist Communities (OECs). Although these communities appear increasingly common, little is known about how these groups form or the methods used to influence them. The work in this thesis provides researchers a methodological framework to study these groups by answering three critical research questions:
• How can we detect large dynamic online activist or extremist communities?
• What automated tools are used to build, isolate, and influence these communities?
• What methods can be used to gain novel insight into large online activist or extremist communities?
This group members social ties can be inferred based on the various affordances offered by OSNs for group curation. By developing heterogeneous, annotated graph representations of user behavior I can efficiently extract online activist discussion cores using an ensemble of unsupervised machine learning methods. I call this technique Ensemble Agreement Clustering. Through manual inspection, these discussion cores can then often be used as training data to detect the larger community. I present a novel supervised learning algorithm called Multiplex Vertex Classification for network bipartition on heterogeneous, annotated graphs. This methodological pipeline has also proven useful for social botnet detection, and a study of large, complex social botnets used for propaganda dissemination is provided as well. Throughout this thesis, I provide Twitter case studies including communities focused on the Islamic State of Iraq and al-Sham (ISIS), the ongoing Syrian Revolution, the Euromaidan Movement in Ukraine, as well as the alt-Right.

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.

Criminologists have generally agreed that the Internet is not only a tool or resource for right-wing extremists to disseminate ideas and products, but also a site of important identity work, accomplished interactively through the exchange of radical ideas. Online discussion forums, amongst other interactive corners of the Web, have become an essential conduit for the radical right to air their grievances and bond around their “common enemy.” Yet overlooked in this discussion has been a macro-level understanding of the radical discussions that contribute to the broader collective identity of the extreme right online, as well as what constitutes “radical posting behavior” within this context. Drawing from criminal career measures to facilitate this type of analysis, data was extracted from a sub-forum of the most notorious white supremacy forum online, Stormfront, which included 141,763 posts made by 7,014 authors over approximately 15 years. In study one of this dissertation, Sentiment-based Identification of Radical Authors (SIRA), a sentiment analysis-based algorithm that draws from traditional criminal career measures to evaluate authors’ opinions, was used to identify and, by extension, assess forum authors’ radical posting behaviors using a mixed-methods approach. Study two extended on study one by using SIRA to quantify authors’ group-level sentiment about their common enemies: Jews, Blacks, and LGBTQs. Study three further extended on studies one and two by analyzing authors’ radical posting trajectories with semi-parametric group-based modeling. Results highlighted the applicability of criminal career measures to study radical discussions online. Not only did this mixed-methods approach provide theoretical insight into what constitutes radical posting behavior in a white supremacy forum, but it also shed light on the communication patterns that contribute to the broader collective identity of the extreme right online.