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Kenya has “increasingly sought to remove online content”, both through requests and increased regulation, that it deems “immoral” or “defamatory”. Following terrorist attacks on civilian targets in recent years, the country has heightened its efforts around counterterrorism as well as online content regulation. Many of Kenya’s legislations have been criticised by civil society for their “broadness”, “vagueness”, and potential “detrimental implications for freedom of expression”. A proposed social media bill, if enacted, could largely impact social media companies and their users in Kenya, such as through strict regulations on user content.

Today’s youth have almost universal access to the internet and frequently engage in social networking activities using various social media platforms and devices. This is a phenomenon that hate groups are exploiting when disseminating their propaganda. This study seeks to better understand youth exposure to hateful material in the online space by exploring predictors of such exposure including demographic characteristics (age, gender and race), academic performance, online behaviours, online disinhibition, risk perception, and parents/guardians’ supervision of online activities. We implemented a cross-sectional study design, using a paper questionnaire, in two high schools in Massachusetts (USA), focusing on students 14 to 19 years old. Logistic regression models were used to study the association between independent variables (demographics, online behaviours, risk perception, parental supervision) and exposure to hate online. Results revealed an association between exposure to hate messages in the online space and time spent online, academic performance, communicating with a stranger on social media, and benign online disinhibition. In our sample, benign online disinhibition was also associated with students’ risk of encountering someone online that tried to convince them of racist views. This study represents an important first step in understanding youth’s risk factors of exposure to hateful material online.

This study focuses on the formation of far-right online communities on YouTube and whether the rise of three new actors (Pegida, Identitarian movement, AfD) can also be observed with user behavior on YouTube. We map the network of far-right, conspiracy and alternative media channels in the German-language YouTube sphere, how this network evolves over time and identify the topics that users discuss. Our analysis shows that the overall common denominator within the German far-right YouTube sphere is the refugee crisis and the problems associated with it. Furthermore, we show that the community is getting denser and more centralized over time.

Contestation over European integration has been widely studied in the rhetoric of parties, leaders, and movements on the far right in a variety of media. Focusing on Twitter use by far right actors in Western Europe, we apply corpus-aided discourse analysis to explore how imaginative geographies are used to politicize Europe among their digital publics. We find that the idea of a crisis of cultural identity pervades imaginaries of Europe amongst far right digital publics. While Europe is presented as facing a crisis of cultural identity, we find that the far right articulates an aspirational imaginary of Europe, the ‘Europe des Nations’ that rejects liberal-democratic pluralism in the EU and the ‘establishment’. We find that the contestation of Europe in far right digital publics relies on a crisis of cultural identity, representing a translation of Nouvelle Droite imaginaries of Europe into the social media space.

In 2020, OpenAI developed GPT-3, a neural language model that is capable of sophisticated natural language generation and completion of tasks like classification, question-answering, and summarization. While OpenAI has not opensourced the model’s code or pre-trained weights at the time of writing, it has built an API to experiment with the model’s capacity. The Center on Terrorism, Extremism, and Counterterrorism (CTEC) evaluated the GPT-3 API for the risk of weaponization by extremists who may attempt to use GPT-3 or hypothetical unregulated models to amplify their ideologies and recruit to their communities.

Recent elections in Europe have demonstrated a steady rise in the success of right-wing populist parties. While advancing an anti-immigration agenda, these parties have been adamant to distance themselves from ‘right-wing extremism’. This article analyses a sample of tweets collected from the Twitter accounts of the German AfD, Identitarian Movement and the Autonomous Nationalists by employing frame analysis. We conclude that the frames of far-right actors classified as extremist, New Right, and populist in fact converge and we discuss our findings in the context of related case studies in other European countries.