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This policy brief traces how Western right-wing extremists have exploited the power of the internet from early dial-up bulletin board systems to contemporary social media and messaging apps. It demonstrates how the extreme right has been quick to adopt a variety of emerging online tools, not only to connect with the like-minded, but to radicalise some audiences while intimidating others, and ultimately to recruit new members, some of whom have engaged in hate crimes and/or terrorism. Highlighted throughout is the fast pace of change of both the internet and its associated platforms and technologies, on the one hand, and the extreme right, on the other, as well as how these have interacted and evolved over time. Underlined too is the persistence, despite these changes, of rightwing extremists’ online presence, which poses challenges for effectively responding to this activity moving forward.

Since the inception of the World Wide Web, security agencies, researchers, and analysts have focused much of their attention on the sentiment found on hate-inspired web-forums. Here, one of their goals has been to detect and measure users’ affects that are expressed in the forums as well as identify how users’ affects change over time. Manual inspection has been one way to do this; however, as the number of discussion posts and sub-forums increase, there has been a growing need for an automated system that can assist humans in their analysis. The aim of this paper, then, is to detect and measure a number of affects expressed in written text on Stormfront.org, the most visited hate forum on the Web. To do this, we used a machine learning approach where we trained a model to recognize affects on three sub-forums: Ideology and Philosophy, For Stormfront Ladies Only, and Stormfront Ireland. The training data consisted of manual annotated data and the affects we focused on were racism, aggression, and worries. Results indicate that even though measuring affects is a subjective process, machine learning is a promising way forward to analyze and measure the presence of different affects on hate forums.

VOX-Pol Blog post.

VOX-Pol Blog post.

VOX-Pol Blog post.

VOX-Pol Blog post.