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Der Rechtsterrorismus ist im digitalen Zeitalter angekommen. Von Christchurch bis El Paso haben sich neue Ausdrucksformen rechter Gewalt etabliert, deren Täter mehr in digitalen Subkulturen als in rechtsextremen Organisationen zu verorten sind. Die radikalisierenden Tendenzen obskurer Online-Communitys geraten somit stärker in den Fokus der Forschung und fordern das Verständnis von rechtem Terror heraus. Wie verändert sich der Rechtsterrorismus also im digitalen Zeitalter? Mit diesem Beitrag möchten wir diese Frage mit dem Verweis auf die Beziehung von digitalen Hasskulturen und rechtsterroristischer Gewalt beleuchten. Wir argumentieren, dass die Analyse der Gewalttaten nicht ohne das Verständnis digitaler Hasskulturen auskommt, die Menschenfeindlichkeit über ironische Kommunikationsformate normalisiert. Aus ihnen heraus bildet sich eine rechtsterroristische Subkultur, die die ambivalenten Erzeugnisse digitaler Kulturen aufgreift und mit gewaltverherrlichenden Inhalten des Neonazismus verbindet, um eines zu erreichen: Menschen zur Gewalt anzuspornen.

Intentional misinformation is a problem that has been documented in a variety of shapes and forms for thousands of years and continues to plague the American landscape. The advent and increasing usage of the Internet have created an additional venue through which intentional misinformation is disseminated, and many groups are taking full advantage of this new communication medium. Because the Internet allows anyone with web publishing skills to disseminate misinformation, it is often difficult for users to judge the credibility of the information. Hate groups understand this phenomenon and are taking full advantage of the Internet by publishing hate sites that promote their extremist ideologies by using language and symbolism that makes the true message difficult to decipher. This study will investigate the methods employed by hate groups to disseminate misinformation to the public.

Does social media lead vulnerable individuals to resort to violence? Many people believe it
does. And they respond with online censorship, surveillance and counter-speech. But what
do we really know about the Internet as a cause, and what do we know about the impact
of these reactions? All over the world, governments and Internet companies are making
decisions on the basis of assumptions about the causes and remedies to violent attacks. The
challenge is to have analysis and responses firmly grounded. The need is for a policy that is
constructed on the basis of facts and evidence, and not founded on hunches – or driven by
panic and fearmongering.
It is in this context that UNESCO has commissioned the study titled Youth and Violent
Extremism on Social Media – Mapping the Research. This work provides a global mapping
of research (mainly during 2012-16) about the assumed roles played by social media in
violent radicalization processes, especially when they affect youth and women. The research
responds to the belief that the Internet at large is an active vector for violent radicalization
that facilitates the proliferation of violent extremist ideologies. Indeed, much research
shows that protagonists are indeed heavily spread throughout the Internet. There is a
growing body of knowledge about how terrorists use cyberspace. Less clear, however, is
the impact of this use, and even more opaque is the extent to which counter measures are
helping to promote peaceful alternatives. While Internet may play a facilitating role, it is not
established that there is a causative link between it and radicalization towards extremism,
violent radicalization, or the commission of actual acts of extremist violence.

VOX-Pol Blog Post.

The purpose of this paper is to discuss the design, application and findings of a case study in which the application of a machine learning algorithm is utilised to identify the grievances in Twitter in an Arabian context. To understand the characteristics of the Twitter users who expressed the identified grievances, data mining techniques and social network analysis were utilised. The study extracted a total of 23,363 tweets and these were stored as a data set. The machine learning algorithm applied to this data set was followed by utilising a data mining process to explore the characteristics of the Twitter feed users. The network of the users was mapped and the individual level of interactivity and network density were calculated. Findings The machine learning algorithm revealed 12 themes all of which were underpinned by the coalition of Arab countries blockade of Qatar. The data mining analysis revealed that the tweets could be clustered in three clusters, the main cluster included users with a large number of followers and friends but who did not mention other users in their tweets. The social network analysis revealed that whilst a large proportion of users engaged in direct messages with others, the network ties between them were not registered as strong. Borum (2011) notes that invoking grievances is the first step in the radicalisation process. It is hoped that by understanding these grievances, the study will shed light on what radical groups could invoke to win the sympathy of aggrieved people. In combination, the machine learning algorithm offered insights into the grievances expressed within the tweets in an Arabian context. The data mining and the social network analyses revealed the characteristics of the Twitter users highlighting identifying and managing early intervention of radicalisation.

What characterises social media radicals? And why some people become attracted to radicalisation? To explore answers to these questions, a number of tweets posted by a group of suspected radicals tweeting in Arabic were analysed using social network analysis and machine learning. The study revealed that these suspected radicals’ networks showed significant interaction with others; but this interactivity is only significant quantitatively as the interaction is not reciprocated. With regards to why these suspected radicals became attracted to radicalisation, Topic Modelling revealed these suspected radicals’ tweets underpinned a perceived injustice that they believed the Secret Police and the Government inflicted upon them. Overall, the study has shown that data science tools have the potential to inform our understanding of online radicalisation. It is hoped this exploratory study will be the basis for a future study in which the research questions will be answered using a larger sample.