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Internet memes have become a popular form through which northern Chileans express frustrations with their marginalization on global, national, and local levels. At the same time, many of these memes criticize Bolivian immigrants for using resources and taking jobs from “true Chileans.” The humorous nature of these texts mitigates the extremity of embedded racial and nationalist ideologies, which are more explicitly expressed in political speech, news media, and quotidian language. This article uses critical discourse analysis to trace ideological formations across multiple online and offline instantiations, making visible a continuum of extreme speech. Through these connections, we see how anti-immigrant discourses position northern residents in a formation of nested marginality. Memes are thus a central way that disenfranchised Chilean citizens reinforce a worldview in which they consider themselves deserving of greater access to resources than Bolivians, precisely because of their marginalized position in relation to the nation.

This article looks at extreme speech practices in Danish weblogs and Facebook comment threads that treat issues of refugees, migration, Islam, and opponents as a cultural war of values and conflict. The article highlights the ritualized ways in which anti-immigrant sentiments are being communicated, received, and responded to. Such recurrent ritualistic communicative patterns include the use of a distinct indignant tone, sarcasm, racialized reasoning, and the use of “high-fives,” as well as a general indifference to facts. The article argues that these online speech patterns can best be understood as a form of “ritualized opposition” that relies on extremist, divisive use of language and naturalization of racialized difference in its attempt to recruit and consolidate communities of support.

This book is a timely and significant examination of the role of counter-messaging via social media as a potential means of preventing or countering radicalization to violent extremism. In recent years, extremist groups have developed increasingly sophisticated online communication strategies to spread their propaganda and promote their cause, enabling messages to be spread more rapidly and effectively. Countermessaging has been promoted as one of the most important measures to neutralize online radicalizing influences and is intended to undermine the appeal of messages disseminated by violent extremist groups. While many such initiatives have been launched by Western governments, civil society actors, and private companies, there are many questions regarding their efficacy. Focusing predominantly on efforts countering Salafi-Jihadi extremism, this book examines how feasible it is to prevent or counter radicalization and violent extremism with counter-messaging efforts. It investigates important principles to consider when devising such a program. The authors provide both a comprehensive theoretical overview and a review of the available literature, as well as policy recommendations for governments and the role they can play in counter-narrative efforts. As this is the first book to critically examine the possibilities and pitfalls of using counter-messaging to prevent radicalization or stimulate de-radicalization, it is essential reading for policymakers and professionals dealing with this issue, as well as researchers in the field.

Social media companies have long struggled with what to do about extremist content on their platforms. While most companies include provisions about “extremist” content in their community standards, until recently, such content was often vaguely defined, providing policymakers and content moderators a wide berth in determining what to remove, and what to allow. Unfortunately, companies have responded with overbroad and vague policies and practices that have led to mistakes at scale that are decimating human rights content.

This paper provides recommendations for what government and social media companies can do in the context of Jammu and Kashmir’s developing online theatre of both potential radicalisation and recruitment

Identification and classification of extremist-related tweets is a hot issue. Extremist gangs have been involved in using social media sites like Facebook and Twitter for propagating their ideology and recruitment of individuals. This work aims at proposing a terrorism-related content analysis framework with the focus on classifying tweets into extremist and non-extremist classes. Based on user-generated social media posts on Twitter, we develop a tweet classifcation system using deep learning-based sentiment analysis techniques to classify the tweets as extremist or non-extremist. The experimental results are encouraging and provide a gateway for future researchers.