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Involuntary celibates, or incels, have been of heightened interest to scholars and practitioners due to their ongoing engagement in misogynistic and violent discourse. The incel subculture is complex, requiring unique strategies to develop effective interventions. The present study investigates patterns in incels’ online posting behaviors and whether acceptance of subcultural beliefs is reflected in variations of user engagement and posting behaviors over time. A sample of postings are drawn from a well-known incel-moderated forum and analyzed using group-based trajectory modeling. The results demonstrate that three distinct posting trajectory groups are present. The findings demonstrate heterogeneity among users’ posting behaviors in the forum over time and suggest that variation may be a reflection of users’ subcultural beliefs.

The use of the Internet as a vehicle of socialization has exploded in the 21st century and while this presents exciting possibilities, it also comes with troubling ones. Among those who have embraced this new medium are extremist groups, who use the Web as a space in which to communicate, exchange ideas, network and reach new followers. In regards to this last point, it provides them near unlimited opportunities to gain access to potential recruits and converts, raising interesting questions in terms of the dynamics of the radicalization process and how it manifests itself within the confines of this new arena. Through an analysis of postings made to the discussion board of Stormfront.org, this research paper examines whether or not the radicalization process follows the same transformative pattern in the virtual world as has been described in some of the leading academic theories that address this phenomenon in the physical one.

It is now widely understood that extremists use the Internet in attempts to accomplish many of their objectives. In this chapter we present a web-crawler called the Terrorism and Extremism Network Extractor (TENE), designed to gather information about extremist activities on the Internet. In particular, this chapter will focus on how TENE may help differentiate terrorist websites from anti-terrorist websites by analyzing the context around the use of predetermined keywords found within the text of the webpage. We illustrate our strategy through a content analysis of four types of web-sites. One is a popular white supremacist website, another is a jihadist website, the third one is a terrorism-related news website, and the last one is an official counterterrorist website. To explore differences between these websites, the presence of, and context around 33 keywords was examined on both websites. It was found that certain words appear more often on one type of website than the other, and this may potentially serve as a good method for differentiating between terrorist websites and ones that simply refer to terrorist activities. For example, words such as “terrorist,” “security,” “mission,” “intelligence,” and “report,” all appeared with much greater frequency on the counterterrorist website than the white supremacist or the jihadist websites. In addition, the white supremacist and the jihadist websites used words such as “destroy,” “kill,” and “attack” in a specific context: not to describe their activities or their members, but to portray themselves as victims. The future developments of TENE are discussed.

This project aims to understand, through a gender and intersectional lens, how socialisation processes coupled with exposure to harassment, hate-based discrimination and extreme content can potentially lower resilience to radicalisation in gaming.

As violent extremists continue to surface in online discussion forums, law enforcement agencies search for new ways of uncovering their digital indicators. Researchers have both described and hypothesized a number of ways to detect online traces of potential extremists, yet this area of inquiry remains in its infancy. This study proposes a new search method that, through the analysis of sentiment, identifies the most radical users within online forums. Although this method is applicable to web-forums of any type, the method was evaluated on four Islamic forums containing approximately 1 million posts of its 26,000 unique users. Several characteristics of each user’s postings were examined, including their posting behavior and the content of their posts. The content was analyzed using Parts-Of-Speech tagging, sentiment analysis, and a novel algorithm called ‘Sentiment-based Identification of Radical Authors’, which accounts for a user’s percentile score for average sentiment score, volume of negative posts, severity of negative posts, and duration of negative posts. The results suggest that there is no simple typology that best describes radical users online; however, the method is flexible enough to evaluate several properties of a user’s online activity that can identify radical users on the forums.