Online Library

Inaugural VOX-Pol Conference:
‘Violent Online Political Extremism: Setting a Research Agenda’
Kings College London: August 28-29, 2014

Focusing on extreme-right organisations in Italy, this article addresses the specific use of the Internet by extremist groups and its potential role for the formation of collective identity, organisational contacts and mobilisation. The analysis includes both political parties and non-party organisations, even violent groups. Through the combination of Social Network Analysis (SNA) of web linkages amongst approximately 100 organisations, with a formalised content analysis of those websites, we argue that various forms of usage of the Internet by right-wing organisations are indeed on the rise,
with an increase not only in the number of extremist websites but also in the exploitation of the Internet for diffusing propaganda, promoting ‘virtual communities’ of debate, fundraising, and organising and mobilising political campaigns. The various specificities of the usage of the Internet by extreme right organisations are demonstrated and linked to offline reality.

How do right-wing extremist organisations throughout the world use the Internet as a tool for communication and recruitment? What is its role in identity-building within radical right-wing groups and how do they use the Internet to set their agenda, build contacts, spread their ideology and encourage mobilization? This important contribution to the field of Internet politics adopts a social movement perspective to address and examine these important questions. Conducting a comparative content analysis of more than 500 extreme right organizational web sites from France, Germany, Italy, Spain, the United Kingdom and the United States, it offers an overview of the Internet communication activities of these groups and systematically maps and analyses the links and structure of the virtual communities of the extreme right. Based on reports from the daily press the book presents a protest event analysis of right wing groups’ mobilisation and action strategies, relating them to their online practices. In doing so it exposes the new challenges and opportunities the Internet presents to the groups themselves and the societies in which they exist.

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.

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.