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This study offers an empirical insight into terrorists’ use of the Internet. Although criminology has previously been quiet on this topic, behavior‐based studies can aid in understanding the interactions between terrorists and their environments. Using a database of 231 US‐based Islamic State terrorists, four important findings are offered: (1) This cohort utilized the Internet heavily for the purposes of both networking with co‐ideologues and learning about their intended activity. (2) There is little reason to believe that these online interactions are replacing offline ones, as has previously been suggested. Rather, terrorists tend to operate in both domains. (3) Online activity seems to be similar across the sample, regardless of the number of co‐offenders or the sophistication of attack. (4) There is reason to believe that using the Internet may be an impediment to terrorists’ success.

The report begins by outlining some of the broad knowledge around the idea of mass persuasion, before focusing specifically on lessons that have been learned in the field of P/CVE. This is followed by a synthesis of existing “How To” guides for the creation of strategic communications from a range of policy and practitioner stakeholders. Then, we discuss specific knowledge of audiovisual content, particularly considerations for short-form video content. The report concludes by outlining how stakeholders, including social media platforms, can monitor, measure, and evaluate the impact of this type of content.

This guide is intended to help creators producing or thinking about making shortform video content seeking to counter extremism. Our goal is not to tell you what to create; your original content is what makes your channel creative and organic. Instead, we hope to provide you with tools and tips to create stronger content that harnesses evidence from decades of academic research. Creating short-form video content (with expected video length to be 15-60 seconds) that counters extremism (both violent and nonviolent) and promotes positive values is a powerful way to engage with your audience. To help you succeed in this mission, we have compiled a guide that not only inspires creativity but also provides practical tips for further success.

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.