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Incels are a sub-culture community of men who forge a sense of identity around their perceived inability to form sexual or romantic relationships. In recent years, there has been a small, but growing, number of violent attacks that have been attributed to individuals who identify as incels. The purpose of this study was to use a large sample of incels from the UK and US to establish (a) their demographic make-up; (b) the consistency of their attitudes and beliefs; (c) their adherence to a common world view, (d) how they network with other incels; (e) whether there are cross-cultural differences between incels from the UK and US in the above; and finally, whether there is a predictive relationship between incel mental health, networking and ideology and the extent of their harmful attitudes and beliefs.

VOX-Pol Blog Post.

Researchers and pundits alike regularly describe terrorism as being a theatrical performance that depends on publicity to build recognition, garner attention and command legitimation. Clearly, the mechanical contours of the information environment matter when it comes to determining the opportunities and challenges for both terrorist and counterterrorist success. This article addresses arguably the most singularly significant intermediary for information access in modern society: web search engines. These information gatekeepers play a crucial role in guiding both government and non-state approaches to terror. That said, these tools are associated with bias and malperformance on a number of fronts. This study examines the degree to which different search engine usage might present a differential view of terrorism to different users. I turn to agent-based digital infrastructure as a basis for studying divergent information experiences with a major terrorist incident, specifically the suicide bombing and subsequent small arms attacks on the Hamid Karzai International Airport in Kabul, Afghanistan on August 26, 2021. The results are striking, confirming that there is substantial and clear variation in the outputs based around a host of factors—variable queries and query styles, information orientations and subsequent personalization, geographic location and, of course, search engine choice.

This study takes a systemic functional multimodal social semiotic approach to the analysis and discussion of image and text relations in two sets of data. First, patterns of contextualisation of images and text in the online magazines Dabiq and Rumiyah produced by the Islamic extremist organisation which refers to itself as Islamic State (referred to here as ISIS) are examined. The second data set consists of a sample of texts from Western online news and blog sites which include recontextualisations of images found in the first data set. A sample of examples of the use and re-use of images is discussed in order to identify patterns of similarity and difference when images and text are recontextualised. It is argued that the ISIS material tends to foreground the interpersonal metafunction in combination with the textual metafunction (i.e. the stance towards the content and the organisation of the message for this purpose), while the other data set tends to foreground the ideational metafunction (the participants, processes and circumstances of what is being reported). These inferences indicate that further exploration of a larger data set is worth pursuing. Such studies would provide deeper insights helping to distinguish between online material which supports terrorism and that which opposes it, as well as facilitating the further development of multimodal social semiotic approaches to image and text relations.

This paper reports on a study that is part of a project which aims to develop a multimodal analytical approach for big data analytics, initially in the context of violent extremism. The findings reported here tested the application of natural language processing models to the text of a sample of articles from the online magazines Dabiq and Rumiyah, produced by the Islamic extremist organisation ISIS. For comparison, text of articles found by reverse image search software which re-used the lead images from the original articles in text which either reported on or opposed extremist activities was also analysed. The aim was to explore what insights the natural language processing models could provide to distinguish between texts produced as propaganda to incite violent extremism and texts which either reported on or opposed violent extremism. The results showed that some valuable insights can be gained from such an approach and that these results could be improved through integrating automated analyses with a theoretical approach with analysed language and images in their immediate and social contexts. Such an approach will inform the interpretation of results and will be used in training software so that stronger results can be achieved in the future.

Two notable features of the current conflict in Syria and Iraq are the number of foreign fighters from western countries fighting for Sunni militant organisations, and the use of the Internet and social media by some extremist groups to disseminate propaganda material. This article explores how the group which refers to itself as Islamic State and an affiliated British group, Rayat al Tawheed, deploy combinations of images and text which serve as bonding icons to rally supporters. The data consists of the English language edition of ISIS’s online magazine Dabiq and online materials produced by Rayat al Tawheed. The results suggest that ISIS and Rayat al Tawheed adopt similar but different iconisation strategies. While ISIS adopts a global strategy to present a unified world view utilising a range of ISIS values in its iconisation, Rayat al Tawheed foregrounds jihad using strategies specifically targeting young, English-speaking men of Islamic/Arab backgrounds.