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We conduct an ethnographic content analysis to examine the social interaction and racial identity constructed through the exchange of white supremacist humor shared on three Stormfront discussion subforums. Overall, white supremacist joke sharing functioned multidimensionally as it simultaneously fostered cohesion and contention among users. By mocking political correctness and non-Whites through the circulation of humorous images and text, white supremacists establish a communal atmosphere and produce a sense of solidarity among members in a more “fun” way than conventional speeches or publications. At the same time, joke sharing may serve as a source of contention when users exchange jokes that violate collective identity norms, such as sharing “blonde jokes” that disparage White females. These findings underscore the ongoing necessity among members of the white supremacist movement to negotiate different ideological tenets. By attending to the social function of white supremacist joke sharing, insights derived from this investigation move beyond more formal social movement events such as marches and demonstrations by attending to the daily activities that white supremacists utilize to resist external threats.

The present Trends Alert was prepared by CTED in accordance with Security Council resolution 2395 (2017). This reaffirms the essential role of CTED within the United Nations to identify and assess issues, trends and developments relating to the implementation of Council resolutions 1373 (2001), 1624 (2005) and 2178 (2014) and other relevant resolutions. CTED Trends Alerts are designed to increase awareness, within the Security Council Counter Terrorism Committee, and among United Nations agencies and policymakers, of emerging trends identified through CTED’s engagement with Member States on their implementation of the relevant Council resolutions. The Alerts also include relevant evidence-based research conducted by members of the CTED Global Research Network (GRN)1 and other researchers.

Reciprocal radicalisation is the theory that extremist organisations are connected and feed on one another’s rhetoric and actions to justify violent escalation. Recent empirical work has suggested that reciprocal radicalisation is a good deal more subtle than is often assumed, and is nuanced by organisational, social and political context. This study seeks to apply the theory of reciprocal radicalisation to the far-right digital milieu, an online space conceptualised as underpinning the varying physical manifestations of the far-right. Based on a qualitative thematic analysis of user posts in three far-right web forums, the study concludes that responses to ideologically opposed terrorism within the far-right milieu are often at odds with the assumed radicalising effects of terrorist attacks. While responses were not uniform, for many users in the far-right digital milieu, jihadist terrorism was an obvious and expected result of the wider failures of politics and society. Although there were some calls for violent reprisal, they were juxtaposed by non-violent responses which interpreted jihadist terror as a consequence and sign of societal decadence and political weakness around issues of migration and rights.

VOX-Pol Blog post.

Security informatics and intelligence computation plays a vital role in detecting and classifying terrorism contents in the web. Accurate web content classification using the computational intelligence and security informatics will increase the opportunities of the early detection of the potential terrorist activities. In this paper, we propose a modified frequency-based term weighting scheme for accurate Dark Web content classification. The proposed term weighting scheme is compared to the common techniques used in text classification such as Term Frequency (TF), Term Frequency-Inverse Document Frequency (TF-IFD), and Term Frequency- Relative Frequency (tf.rf), on a dataset selected from Dark Web Portal Forum. The experimental results show that the classification accuracy and other evaluation measures based on the proposed scheme outperforms other term weighting techniques based classification.

VOX-Pol Blog Post.