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Contemporary research has highlighted the steady rise of individuals becoming radicalised via exposure to extremist discussion on the internet, with the ease of communication with other users that the internet provides playing a major role in the radicalisation process of these individuals. The aim of the present systematic review was to explore recent research into the utilisation of language in extremist cyberspaces and how it may influence the radicalisation process. The findings suggest that there are five prominent linguistical behaviours adopted by extremists online: Algorithmic, Conflict, Hate, Positive, and Recruitment. The results demonstrate that the main purpose of extremist language online is to shape the perceptions of users to see their associated group in positive regard, while simultaneously negatively framing outgroup opposition. This is then followed by encouraging conflict against the promoted ideologies’ perceived enemies. Limitations, future research, and implications are discussed in detail.

The aim of the report is to determine the overlaps apparent in the far-right scene on Twitter, and specifically, to ascertain the extent to which different groups on the scene are indeed talking about the same issues in the same way, in spite of apparent differences in tone and underlying ideologies. The authors utilise a mixed-methods approach: first, gaining a cursory insight into the extreme right-wing scene on Twitter across Europe; and then applying a detailed frame analysis to three selected groups in Germany to determine the implicit and explicit overlaps between them, thus complementing the quantitative findings to offer an in-depth analysis of meaning.

VOX-Pol Blog post.

VOX-Pol Blog post.

VOX-Pol Blog post.

VOX-Pol Blog post.