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The global war on terror (“GWOT”) is being fought on many levels. In addition to traditional terror and counterterror activity, both sides are engaged in a public relations and propaganda war, employing the media, willingly and unwillingly, to support their positions. Hovering over these war campaigns are information technologies, which include the Internet. This article provides an introduction to various online content concealing practices that have been employed by those seeking to conceal or limit access to information on the Internet, including terrorist organizations. Further, there is a discussion on tracking and monitoring of website visitors. After reviewing open source information and websites, this article examines techniques and technologies that are easily available to terrorist organizations — foreign and domestic — whose structure can be obtained through Internet websites. The article then turns to a discussion of the legal issues posed by active and passive website monitoring techniques.

In this Perspective, the authors introduce a framework for internet users to categorize the virtual platforms they use and to understand the likelihood that they may encounter extreme content online. The authors first provide a landscape of the online extremist “ecosystem,” describing how the proliferation of messaging forums, social media networks, and other virtual community platforms has coincided with an increase in extremist online activity. Next, they present a framework to describe and categorize the platforms that host varying amounts of extreme content as mainstream, fringe, or niche. Mainstream platforms are those for which only a small portion of the content would be considered inappropriate or extreme speech. Fringe platforms are those that host a mix of mainstream and extreme content—and where a user might readily come across extreme content that is coded or obscured to disguise its violent or racist underpinning. Niche platforms are those that openly and purposefully cater to an extreme audience.

VOX-Pol Blog post.

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.

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.

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.