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This article presents a mixed methods approach for analysing text and image relations in violent extremist discourse. The approach involves integrating multimodal discourse analysis with data mining and information visualisation, resulting in theoretically informed empirical techniques for automated analysis of text and image relations in large datasets. The approach is illustrated by a study which aims to analyse how violent extremist groups use language and images to legitimise their views, incite violence, and influence recruits in online propaganda materials, and how the images from these materials are re-used in different media platforms in ways that support and resist violent extremism. The approach developed in this article contributes to what promises to be one of the key areas of research in the coming decades: namely the interdisciplinary study of big (digital) datasets of human discourse, and the implications of this for terrorism analysis and research.

This briefing is part of ISD’s Gaming and Extremism Series exploring the role online gaming plays in the strategy of far-right extremists in the UK and globally. This is part of a broader programme on the ‘Future of Extremism’ being delivered by ISD in the second half of 2021, charting the transformational shifts in the extremist threat landscape two decades on from 9/11, and the policy strategies required to counter the next generation of extremist threats. It provides a snapshot overview of the extreme right’s use of Twitch.

This report aims to provide an in-depth analysis on the state of extremism and hate on TikTok. It is the culmination of three months of research on a sample of 1,030 videos, equivalent to just over eight hours of content, posted on the social media platform. These videos were used to promote hatred, as well as glorify extremism and terrorism.

ISD set out to examine the state of hate and extremism on TikTok in two ways. The first objective involved analysing how individuals or groups promote hateful ideologies and target people on the platform based on numerous protected attributes such as ethnicity, religion, gender or others. Second, using the same framework, ISD investigated how features on TikTok like profiles, hashtags, share functions, video effects and music are used to spread hate.

This report seeks to start a conversation around how platforms like TikTok can improve their own practices to protect users from harm. Additionally, it underscores the clear need for independent oversight of such platforms, which currently leave users and the wider public open to significant risks to their health, security and rights.

The Syria conflict has been described as the most socially mediated in history, with online social media playing a particularly important role. At the same time, the everchanging landscape of the conflict leads to difficulties in applying analytical approaches taken by other studies of online political activism. Therefore, in this paper, we use an approach that does not require strong prior assumptions or the proposal of an advance hypothesis to analyze Twitter and YouTube activity of a range of protagonists to the conflict, in an attempt to reveal additional insights into the relationships between them. By means of a network representation that combines multiple data views, we uncover communities of accounts falling into four categories that broadly reflect the situation on the ground in Syria. A detailed analysis of selected communities within the antiregime categories is provided, focusing on their central actors, preferred online platforms, and activity surrounding “real world” events. Our findings indicate that social media activity in Syria is considerably more convoluted than reported in many other studies of online political activism, suggesting that alternative analytical approaches can play an important role in this type of scenario.

Recent years have seen increased interest in the online presence of extreme right groups. Although originally composed of dedicated websites, the online extreme right milieu now spans multiple networks, including popular social media platforms such as Twitter, Facebook and YouTube. Ideally therefore, any contemporary analysis of online extreme right activity requires the consideration of multiple data sources, rather than being restricted to a single platform. We investigate the potential for Twitter to act as one possible gateway to communities within the wider online network of the extreme right, given its facility for the dissemination of content. A strategy for representing heterogeneous network data with a single homogeneous network for the purpose of community detection is presented, where these inherently dynamic communities are tracked over time. We use this strategy to discover and analyse persistent English and German language extreme right communities.

Many extreme right groups have had an online presence for some time through the use of dedicated websites. This has been accompanied by increased activity in social media websites in recent years, which may enable the dissemination of extreme right content to a wider audience. In this paper, we present exploratory analysis of the activity of a selection of such groups on Twitter, using network representations based on reciprocal follower and mentions interactions. We find that stable communities of related users are present within individual country networks, where these communities are usually associated with variants of extreme right ideology. Furthermore, we also identify the presence of international relationships between certain groups across geopolitical boundaries.