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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.

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.

Within a fairly short amount of time, the Islamic State of Iraq and Syria (ISIS) has managed to put large swaths of land in Syria and Iraq under their control. To many observers, the sheer speed at which this “state” was established was dumbfounding. To better understand the roots of this organization and its supporters we present a study using data from Twitter. We start by collecting large amounts of Arabic tweets referring to ISIS and classify them into pro-ISIS and anti-ISIS. This classification turns out to be easily done simply using the name variants used to refer to the organization: the full name and the description as “state” is associated with support, whereas abbreviations usually indicate opposition. We then “go back in time” by analyzing the historic timelines of both users supporting and opposing and look at their pre-ISIS period to gain insights into the antecedents of support. To achieve this, we build a classifier using pre-ISIS data to “predict”, in retrospect, who will support or oppose the group. The key story that emerges is one of frustration with failed Arab Spring revolutions. ISIS supporters largely differ from ISIS opposition in that they refer a lot more to Arab Spring uprisings that failed. We also find temporal patterns in the support and opposition which seems to be linked to major news, such as reported territorial gains, reports on gruesome acts of violence, and reports on airstrikes and foreign intervention.

Young People Combating Hate Speech Online is a project of the Council of Europe’s youth sector running between 2012 and 2015. The project aims to combat racism and discrimination in their online expression of hate speech by equipping young people and youth organisations with the competences necessary to recognize and act against such human rights violations. Central to the project is a European youth media campaign which will be designed and  implemented with the agency of young people and youth organisations. As a preparation for the project, the Council of Europe’s Youth Department commissioned three “mapping” studies about the realities of hate speech and young people and projects and campaigns about it. These studies are published here as a resource for the activists, youth leaders, researchers, partners and decision makers associated to the project and the online campaign. They are truly a starting points: more research is needed, both on the legal and policy implications of hate speech online as on its impact and relation with young people.

The internet permeates all aspects of modern life and violent extremism is no exception. Although the level of importance is sometimes disputed, few would deny the role that online communication has in driving people towards violent extremist groups. While there are various perspectives on the exact nature of this process, it is increasingly agreed upon that it is rare for individuals to radicalise entirely in absence of any outside communication. Radicalisation remains a social phenomenon and the fact that some of these social interactions have migrated online does not change this. Extremists do not simply produce and disseminate propaganda and then move straight to offline recruitment, they utilise peer to peer messaging applications contained within social media platforms to engage in direct personal contact with potential recruits to their cause. Sometimes these online conversations completely displace offline recruitment.

Extremist propaganda is often removed and there are examples of nascent efforts to counter this throught the creation of counter-narrative campaigns. Counter-narratives, and offline counter-recruitment programmes such as EXIT and Channel, counter efforts of extremists to promote propaganda online and recruit in the offline world. This highlights the fact that there is a crucial piece missing in our efforts to counter recruitment to extremist groups; the proactive utilisation of peer to peer messaging systems online to engage with those expressing extremist sympathies.

Over the course of ISD’s management of the AVE network we encountered a number of isolated attempts to engage directly with extremists online, from former extremists infiltrating extremist forums to Twitter conversations between activists and extremist sympathisers. However none of these efforts had been attempted at scale none had had testing and success
metrics built in from the start. As such, any evidence gained as to their effectiveness was anecdotal at best.

This paper explores various Social Network Analysis (SNA) techniques in order to identify a range of potentially ‘important’ members of Islamic Networks within Dark Web Forums. For this experiment, we conducted our investigation on five forums collected in previous work as part of the DarkWeb Forum portal and built upon the tool support created in our previous research in order to visualise and analyse the network. Whilst existing work attempts to identify these structures through state-of-the-art Computational Linguistic techniques, our work relies on the communication metadata alone. Our analysis involved first calculating a range of SNA metrics to better understand the group members, and then apply unsupervised learning in order to create clusters that would help classify the Dark Web Forums users into hierarchical clusters. In order to create our social networks, we investigated the effect of repeated author resolution and various weighting schemes on the ranking of forum members by creating four social networks per forum and evaluating the correlation of the top n users (for n = 10; 20; 30; 40; 50 and 100). Our results identified that varying the weighting schemes created more consistent ranking schemes than varying the repeated author resolution.