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This book offers empirical insight into the way Muslims reacted online towards various controversial issues related to Islam. The book examines four cases studies: The Muhammed’s cartoons, the burning of the Quran controversies, Fitna and the Innocence of Muslims’ films. The issues of online religion, social movements and extremism are discussed, as many of the cases in question created both uproar and unity among many YouTubers. These case studies – in some instances – led to the expression of extremist views by some users, and the volume argues that they helped contribute to the growth of extremism due to the utilization of these events by some terrorist groups in order to recruit new members. In the concluding chapter, social network and sentiment analyses are presented in order to investigate all the collected comments and videos, while a critical discussion of freedom of expression and hate speech is offered, with special regards to the growing online influence of far right groups and their role in on-going YouTube debates.

In this paper we present a multimodal approach to categorizing user posts based on their discussion topic. To integrate heterogeneous information extracted from the posts, i.e. text, visual content and the information about user interactions with the online platform, we deploy graph convolutional networks that were recently proven effective in classification tasks on knowledge graphs. As the case study we use the analysis of violent online political extremism content, a challenging task due to a particularly high semantic level at which extremist ideas are discussed. Here we demonstrate the potential of using neural networks on graphs for classifying multimedia content and, perhaps more importantly, the effectiveness of multimedia analysis techniques in aiding the domain experts performing qualitative data analysis. Our conclusions are supported by extensive experiments on a large collection of extremist posts. This research was produced with the aid of VOX-Pol Research Mobility Programme funding and supervision by VOX-Pol colleagues at Dublin City University.

What explains online radicalization and support for ISIS in the West? Over the past few years, thousands of individuals have radicalized by consuming extremist content online, many of whom eventually traveled overseas to join the Islamic State. This study examines whether anti-Muslim hostility might drive pro-ISIS radicalization in Europe. Using new geo-referenced data on the online behavior of thousands of Islamic State supporters in France, the United Kingdom, Germany, and Belgium, I study whether the intensity of anti-Muslim hostility at the local (neighborhood/municipality) level is linked to pro-ISIS radicalization on Twitter. Results show that local-level measures of anti-Muslim animosity correlate significantly and substantively with indicators of online radicalization, including posting tweets sympathizing with ISIS, describing life in ISIS-controlled territories, discussing foreign fighters, and expressing anti-West sentiment. High-frequency data surrounding events that stir anti-Muslim hostility — terrorist attacks and anti-Muslim protests in Europe — show the same pattern.

Online social media platforms such as Twitter have been found to be misused by extremist groups, including Islamic State of Iraq and Syria (ISIS), who attract and recruit social media users. To prevent their influence from expanding in the online social media platforms, it is required to understand the online behaviors of these extremist group users and their followers, for predicting and identifying potential security threats. We present an empirical study about ISIS followers’ online behaviors on Twitter, proposing to classify their tweets in terms of political and subjectivity polarities. We first develop a supervised classification model for the polarity classification, based on natural language processing and clustering methods. We then develop a statistical analysis of term-polarity correlations, which leads us to successfully observe ISIS followers’ online behaviors, which are in line with the reports of experts.

The rise of the Islamic State has contributed to both an increased terrorism threat in Western nations and an unprecedented number of citizens joining the group of so-called foreign fighters. IS has used the internet as a way to both disseminate propaganda and radicalize and recruit supporters. This article will begin by analyzing some of the most recent and well-known of such efforts, offering explanations for their successes and failures. The author then assesses limitations to combatting extremist ideas. Not only must the solution involve civil society, but a recalibration of the meaning and aims of counter-messaging is needed.

This paper investigates the link between social media and hate crime using hand-collected data from Facebook and Twitter. We study the case of Germany, where the recently emerged right-wing party Alternative für Deutschland (AfD) has developed a major social media presence. Using a difference-in-differences design, we show that right-wing anti-refugee sentiment on Facebook predicts violent crimes against refugees in otherwise similar municipalities with higher social media usage. Consistent with social media being the driving force, the effect decreases with internet outages; increases with user network interactions; is not driven by the news cycle; and does not hold for posts unrelated to refugees. We find similar evidence for the United States, where President Trump’s twitter activity strongly predicts hate crimes against the minorities targeted in his tweets, but not other minorities. We find no effect for the period before Trump’s presidential campaign or measures of general anti-minority sentiment.