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This article is a systematic large-scale study of the reasons driving political fragmentation on social media. Making use of a comparative dataset of the Twitter discussion activities of 115 political groups in 26 countries, it shows that groups that are further apart in ideological terms interact less, and that groups that sit at the extremes of the ideological scale are particularly likely to have lower patterns of interaction. Indeed, exchanges between centrists who sit on different sides of the left–right divide are more likely than connections between centrists and extremists who are from the same ideological wing. In light of the results, theory about exposure to different ideological viewpoints online is enhanced.

The decision to target leaders of groups like ISIS to hamper their effectiveness has served as a longstanding principle of counterterrorism efforts. Yet, previous research suggests that any results may simply be temporary. Using insights from confiscated ISIS documents from Afghanistan to define the media leader roles that qualified for each level of the cascade, CTC (Combating Terrorism Center) records to identify media leaders who died, and a content analysis of all ISIS images displayed in the group’s Arabic weekly newsletter to identify the group’s visual framing strategies, this study assesses whether and how leader loss helps explain changes in the level and nature of the group’s visual output over time. ISIS’s quantity of output and visual framing strategies displayed significant changes before, during, and after media leader losses. The level of the killed leader within the group’s organizational hierarchy also corresponded to different changes in ISIS’s media framing.

This review presents the existing research on the role of the Internet in radicalization processes. Using a systematic literature search strategy, our paper yields 88 studies on the role of the Internet in a) right-wing extremism and b) radical jihadism. Available studies display a predominant interest in the characteristics of radical websites and a remarkable absence of a user-centred perspective. They show that extremist groups make use of the Internet to spread right wing or jihadist ideologies, connect like-minded others in echo chambers and cloaked websites, and address particularly marginalized individuals of a society, with specific strategies for recruitment. Existing studies have thus far not sufficiently examined the users of available sites, nor have they studied the causal mechanisms that unfold at the intersection between the Internet and its users. The present review suggests avenues for future research, drawing on media and violence research and research on social identity and deindividuation effects in computer-mediated communication.

Extreme digital speech (EDS) is an emerging challenge that requires co-ordination between governments, civil society and the private sector. In this report, a range of experts on countering extremism consider the challenges that EDS presents to these stakeholders, the impact that EDS has and the responses taken by these actors to counter it. By focusing on EDS, consideration of the topic is limited to the forms of extreme speech that take place online, often on social media platforms and multimedia messaging applications such as WhatsApp and Telegram. Furthermore, by focusing on EDS rather than explicitly violent forms of extreme speech online, the report departs from a focus on violence and incorporates a broader range of issues such as hateful and dehumanising speech and the complex cultures and politics that have formed around EDS.

Hate groups are increasingly using multiple social media platforms to promote extremist ideologies. Yet we know little about their communication practices across platforms. How do hate groups (or “in-groups”), frame their hateful agenda against the targeted group or the “out-group?” How do they share information? Utilizing “framing” theory from social movement research and analyzing domains in the shared links, we juxtapose the Facebook and Twitter communication of 72 Southern Poverty Law Center (SPLC) designated hate groups spanning five hate ideologies. Our findings show that hate groups use Twitter for educating the audience about problems with the out-group, maintaining positive self-image by emphasizing in-group’s high social status, and for demanding policy changes to negatively affect the out-group. On Facebook, they use fear appeals, call for active participation in group events (membership requests), all while portraying themselves as being oppressed by the out-group and failed by the system. Our study unravels the ecosystem of cross-platform communication by hate groups, suggesting that they use Facebook for group radicalization and recruitment, while Twitter for reaching a diverse follower base.

In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users. It allows the analyst to identify and select users of interest, and to find similar users in an interactive learning setting. Our approach is based on novel multimodal representations of users, words and concepts, which we simultaneously learn by deploying a general-purpose neural embedding model. The usefulness of the approach is evaluated using artificial actors, which simulate user behavior in a relevance feedback scenario. Multiple experiments were conducted in order to evaluate the quality of our multimodal representations and compare different embedding strategies. We demonstrate the capabilities of the proposed approach on a multimedia collection originating from the violent online extremism forum Stormfront, which is particularly interesting due to the high semantic level of the discussions it features.