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Although researchers know a great deal about persuasive messages that encourage terrorism, they know far less about persuasive messages that denounce terrorism and little about how these two sides come together. We propose a conceptualization that distinguishes a message’s support for an act from its support for the ideology underlying an act. Our prediction is tested using corpus-linguistic analysis of 250 counter-extremist messages written by Muslims and U.K. officials and a comparison set of 250 Muslim extremist messages. Consistent with our prediction, Muslim extremist and Muslim counter-messages show disagreement on terrorist actions but agreement in ideological aspects, while U.K. officials’ counter-messages show disagreement with both Muslim extremists’ acts and ideology. Our findings suggest that counter-messages should not be viewed as a homogenous group and that being against violent extremism does not necessarily equate to having positive perceptions of Western values.

The RiskTrack project aims to help in the prevention of terrorism through the identification of online radicalisation. In line with the European Union priorities in this matter, this project has been designed to identify and tackle the indicators that raise a red flag about which individuals or communities are being radicalised and recruited to commit violent acts of terrorism. Therefore, the main goals of this project will be twofold: On the one hand, it is needed to identify the main features and characteristics that can be used to evaluate a risk situation, to do that a risk assessment methodology studying how to detect signs of radicalisation (e.g., use of language, behavioural patterns in social networks…) will be designed. On the other hand, these features will be tested and analysed using advanced data mining methods, knowledge representation (semantic and ontology engineering) and multilingual technologies. The innovative aspect of this project is to not offer just a methodology on risk assessment, but also a tool that is build based on this methodology, so that the prosecutors, judges, law enforcement and other actors can obtain a short term tangible results.

As violent extremists continue to surface in online discussion forums, law enforcement agencies search for new ways of uncovering their digital indicators. Researchers have both described and hypothesized a number of ways to detect online traces of potential extremists, yet this area of inquiry remains in its infancy. This study proposes a new search method that, through the analysis of sentiment, identifies the most radical users within online forums. Although this method is applicable to web-forums of any type, the method was evaluated on four Islamic forums containing approximately 1 million posts of its 26,000 unique users. Several characteristics of each user’s postings were examined, including their posting behavior and the content of their posts. The content was analyzed using Parts-Of-Speech tagging, sentiment analysis, and a novel algorithm called ‘Sentiment-based Identification of Radical Authors’, which accounts for a user’s percentile score for average sentiment score, volume of negative posts, severity of negative posts, and duration of negative posts. The results suggest that there is no simple typology that best describes radical users online; however, the method is flexible enough to evaluate several properties of a user’s online activity that can identify radical users on the forums.

Analyses of extremist video messages typically focus on their discursive content. Using the case of ISIL (Islamic State of Iraq and the Levant), this study instead draws upon the emerging subfield of genosonic analysis to understand the allure of extremist videos, as well as the ineffectiveness of US video messages designed to ‘counter violent extremism’ (CVE). Through a genosonic analysis of three high-profile ISIL videos and five popular US State Department CVE videos, the study advances two concepts – sonorous communality and sonic unmaking – to help explain ISIL’s appeal. The lack of equivalent dimensions in US CVE videos renders them sonically sterile in comparison to those of ISIL. The implications of this analysis for scholarship and practice conducted at the intersection of media, war and conflict are discussed.

The Islamic State of Iraq and Syria (ISIS) has made great use of the Internet and online social media sites to spread its message and encourage others, particularly young people, to support the organization, to travel to the Middle East to engage in combat—fighting side-by-side with other jihadists, or to join the group by playing a supporting role—which is often the role carved out for young women who are persuaded to join ISIS. The terrorist group has even directed sympathizers to commit acts of violence wherever they are when traveling to the Middle East isn’t possible. ISIS propaganda is now more frequently aimed at Westerners and more specifically aimed at the “Millennial generation.”

Clearly, social media has proven to be an extremely valuable tool for the terrorist organization and is perfectly suited for the very audience it’s intending to target. According to Pew Research Center’s Social Networking Fact Sheet, 89% of adults aged 18 – 29 use social media” 1 Platforms such as Facebook and Twitter, and even YouTube, allow ISIS propaganda to reach across the globe in real time. Increasingly, ISIS’ posts to Internet sites include sophisticated, production-quality video and images that incorporate visual effects. What messages from jihadists induce young Westerners to become involved with the terrorist group? What convinces young people from Europe, Australia, Canada, and the United States—many who are technically runaways, still in their teens—to leave their homelands to join ISIS on the battlefield? What risks does a home country face when its nationals communicate and establish relationships with members of ISIS? Can the jihadist social network propaganda machine be shut down, and weighing all factors, is stopping ISIS rhetoric on the Internet the best course of action? This paper explores these and other questions related to terrorist groups’ utilization of social media.

From its start, the so-called Islamic State of Iraq and the Levant (ISIL/ISIS) has been successfully exploiting social media networks, most notoriously Twitter, to promote its propaganda and recruit new members, resulting in thousands of social media users adopting pro-ISIS stance every year. Automatic identification of pro-ISIS users on social media has, thus, become the centre of interest for various governmental and research organisations. In this paper we propose a semantic-based approach for radicalisation detection on Twitter. Unlike most previous works, which mainly rely on the lexical and contextual representation of the content published by Twitter users, our approach extracts and makes use of the underlying semantics of words exhibited by these users to identify their pro/anti-ISIS stances. Our results show that classifiers trained from words’ semantics outperform those trained from lexical and network features by 2% on average F1-measure.