In this paper, I analyze how the so called ‘alt-right’ is using Twitter to mainstream its politics. Understanding alt-right mainstreaming is important because the movement has embraced a Gramscian view of politics that believes cultural change (e.g. normalizing unpopular ideas) must precede institutional change (e.g. fielding candidates for office). To conduct my analysis I created ...

This article seeks to propose a valuable frame for understanding which processes, either cognitive or practical, take part in the making of a terrorist act within the frame of the onlife region. A term recently coined, onlife, refers to the interacting/indistinguishable domain of online and offline world: this is the environment where today’s global terrorism/extremism ...

The number of lone-actor attacks committed by far-right extremists have surged in recent years, most notably in the West where mass-casualty attacks have occurred, including the United States, New Zealand, the United Kingdom, and Germany. The fatal attack in February 2020 in Hanau, Germany, revealed the perpetrator’s influences to be a combination of traditional far-right, ...

In this study, we examine key psychological dimensions in the manifestos authored by the perpetrators of the Christchurch and Utøya massacres, the right-wing extremists Brenton Tarrant and Anders Breivik, and the ISIS propaganda magazine Rumiyah. All texts were authored and disseminated virtually with the purpose of attracting or consolidating support, and justifying violent, discriminatory actions. ...

Hate speech may take different forms in online social media. Most of the investigations in the literature are focused on detecting abusive language in discussions about ethnicity, religion, gender identity and sexual orientation. In this paper, we address the problem of automatic detection and categorization of misogynous language in online social media. The main contribution ...

With the ever-increasing cases of hate spread on social media platforms, it is critical to design abuse detection mechanisms to pro-actively avoid and control such incidents. While there exist methods for hate speech detection, they stereotype words and hence suffer from inherently biased training. Bias removal has been traditionally studied for structured datasets, but we ...

Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist, sexist or neither. The complexity of the natural language constructs makes this task very challenging. We perform extensive experiments with multiple ...

Race and racism persist online in ways that are both new and unique to the Internet, alongside vestiges of centuries-old forms that reverberate significantly both offline and on. As we mark 15 years into the field of Internet studies, it becomes necessary to assess what the extant research tells us about race and racism. This ...

A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. ...

This article applies instruments of social network analysis to a study of communication networks within the Italian and German extremist right. Web links between organizational websites are used as a proxy. Indeed, extremist groups increasingly use and abuse the Internet for their propaganda and their recruitment, and also for their internal communication. The analysis includes ...