Online Library

This article looks at Internet use by insurgent groups in the North Caucasus in the context of a regional diffusion of violence. Using a mixed methods research design that combines hyperlink network analysis and micro-discourse analysis, it examines the online characteristics of the Caucasus Emirate and the main frames conveyed by the websites affiliated with the Emirate. It demonstrates the existence of a network of cross-referencing websites that, collectively, articulate the Emirate’s political agenda online and allow for the dissemination of frames across the Web. It also shows that while jihadism provides a cultural resource that fosters a global sense of community, the jihadization of discourse does not eradicate local references as the local dynamics of the conflict have a strong impact on online communicative strategies. Finally, although based on a specific case study, this article highlights the potential of a mixed methods research design as applied to an analysis of virtual insurgent networks.

Progressive political movements and activists are not the only ones appropriating Web 2.0 as a way to construct independent public spaces and voice counter- hegemonic discourses. By looking at the other extreme of (post-)fascist movements, it will be shown that the internet also gives rise to anti-public spaces, voicing hatred and essentialist discourses. In this article, discourses of hate produced by North- Belgian (post-)fascist movements and activists will be analysed. Theoretically the analysis is informed by radical pluralism and the limits of freedom of speech in a strong democracy. The cases presented challenge the limits of freedom of speech and of radical pluralism and bring us to question whether being a racist is a democratic right, whether freedom of speech includes opinions and views that challenge basic democratic 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.

The permanent transition to online activity has brought with it a surge in hate speech discourse. This has prompted increased calls for automatic detection methods, most of which currently rely on a dictionary of hate speech words, and supervised classification. This approach often falls short when dealing with newer words and phrases produced by online extremist communities. These code words are used with the aim of evading automatic detection by systems. Code words are frequently used and have benign meanings in regular discourse, for instance, “skypes, googles, bing, yahoos” are all examples of words that have a hidden hate speech meaning. Such overlap presents a challenge to the traditional keyword approach of collecting data that is specific to hate speech. In this work, we first introduced a word embedding model that learns the hidden hate speech meaning of words. With this insight on code words, we developed a classifier that leverages linguistic patterns to reduce the impact of individual words. The proposed method was evaluated across three different datasets to test its generalizability. The empirical results show that the linguistic patterns approach outperforms the baselines and enables further analysis on hate speech expressions.

This article applies instruments of social network analysis to a study of communication networks within the Italian and German extremist right. Web links between organizational websites are used as a proxy. Indeed, extremist groups increasingly use and abuse the Internet for their propaganda and their recruitment, and also for their internal communication. The analysis includes both political parties and non-party organizations, even violent groups. In a macro-, micro-, and meso-analysis, the various specificities of the two national political sectors are demonstrated and linked to the offline reality. The Italian network appears to be very fragmented, highly diversified, and difficult to be coordinated (‘policephalous network’), whereas the German network is denser and much more concentrated on a few central actors (‘star structure’). These differences are mainly due to political opportunity structures in the two countries. Additionally, whereas the Italian network structure allows for the construction of a typology of sub-groups of organizations, the German communicative structure seems to be more erratic and less coordinated. The article also highlights the function of websites which are not related to any specific group. Indeed, these are of special importance for the far right as a political arena which is usually banned from the dominant societal discourses (if not even legally forbidden). Considering this, new modes of communication can be of greater use for extremist groups than for more traditional political actors.

This article applies instruments of social network analysis to a study of communication networks within the Italian and German extremist right. Web links between organizational websites are used as a proxy. Indeed, extremist groups increasingly use and abuse the Internet for their propaganda and their recruitment, and also for their internal communication. The analysis includes both political parties and non-party organizations, even violent groups. In a macro-, micro-, and meso-analysis, the various specificities of the two national political sectors are demonstrated and linked to the offline reality. The Italian network appears to be very fragmented, highly diversified, and difficult to be coordinated (‘policephalous network’), whereas the German network is denser and much more concentrated on a few central actors (‘star structure’). These differences are mainly due to political opportunity structures in the two countries. Additionally, whereas the Italian network structure allows for the construction of a typology of sub-groups of organizations, the German communicative structure seems to be more erratic and less coordinated. The article also highlights the function of websites which are not related to any specific group. Indeed, these are of special importance for the far right as a political arena which is usually banned from the dominant societal discourses (if not even legally forbidden). Considering this, new modes of communication can be of greater use for extremist groups than for more traditional political actors.