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VOX-Pol Blog post.

In this study, we select the official websites of four known extremist groups and map the networks of hyperlinked websites forming a virtual community around them. The networks are constructed using a custom-built webcrawler (TENE: Terrorism and Extremism Network Extractor) that searches the HTML of a website for all the hyperlinks inserted directing to other websites (Bouchard et al., 2014). Following all of these hyperlinks out of the initial website of interest produces the network of websites forming a community that is more or less cohesive, more or less extensive, and more or less devoted to the same cause (Bouchard and Westlake, 2016; Westlake and Bouchard, 2016). The extent to which the official website of a group contains many hyperlinks towards external websites may be an indicator of a more active community, and it may be indicative of a more active social movement.

Since the advent of the Internet, right-wing extremists and those who subscribe to extreme right views have exploited online platforms to build a collective identity among the like-minded. Research in this area has largely focused on extremists’ use of websites, forums, and mainstream social media sites, but overlooked in this research has been an exploration of the popular social news aggregation site Reddit. The current study explores the role of Reddit’s unique voting algorithm in facilitating “othering” discourse and, by extension, collective identity formation among members of a notoriously hateful subreddit community, r/The_Donald. The results of the thematic analysis indicate that those who post extreme-right content on r/The_Donald use Reddit’s voting algorithm as a tool to mobilize like-minded members by promoting extreme discourses against two prominent out-groups: Muslims and the Left. Overall, r/The_Donald’s “sense of community” facilitates identity work among its members by creating an environment wherein extreme right views are continuously validated.

The purpose of this paper is to discuss the design, application and findings of a case study in which the application of a machine learning algorithm is utilised to identify the grievances in Twitter in an Arabian context. To understand the characteristics of the Twitter users who expressed the identified grievances, data mining techniques and social network analysis were utilised. The study extracted a total of 23,363 tweets and these were stored as a data set. The machine learning algorithm applied to this data set was followed by utilising a data mining process to explore the characteristics of the Twitter feed users. The network of the users was mapped and the individual level of interactivity and network density were calculated. Findings The machine learning algorithm revealed 12 themes all of which were underpinned by the coalition of Arab countries blockade of Qatar. The data mining analysis revealed that the tweets could be clustered in three clusters, the main cluster included users with a large number of followers and friends but who did not mention other users in their tweets. The social network analysis revealed that whilst a large proportion of users engaged in direct messages with others, the network ties between them were not registered as strong. Borum (2011) notes that invoking grievances is the first step in the radicalisation process. It is hoped that by understanding these grievances, the study will shed light on what radical groups could invoke to win the sympathy of aggrieved people. In combination, the machine learning algorithm offered insights into the grievances expressed within the tweets in an Arabian context. The data mining and the social network analyses revealed the characteristics of the Twitter users highlighting identifying and managing early intervention of radicalisation.

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.

Currently, a gap in the literature exists on the link between radicalization processes and
the social psychology of the Internet. While radicalization processes are increasingly
becoming subject to empirical studies, only a subset of these studies have taken into
account online dynamics, and even fewer have approached this issue from a social psychological
perspective. However, the literature on radicalization to violent extremism clearly establishes
the central role of social psychology. It also suggests that the Internet is increasingly salient for
understanding processes of radicalization. It follows then, that understanding radicalization processes
requires an explanation of how the Internet may influence beliefs and behaviours; that is,
of the social psychology of the Internet.
This report outlines the link between the social psychology of the Internet and violent extremism.
It is divided into two parts. The first part, provides a review of the literature on the
social psychology of the Internet, including its potential applications to the understanding of
violent extremism. This section examines both the individual and collective dimensions involved
when individuals reach out and interact online with like-minded virtual peers, and their effects
on individual and collective behaviours. Concepts defined in the literature review are then applied
to analyze fifteen case studies of individuals whose involvement in violent extremist acts
has been confirmed, and where the Internet played a role, small or large, in their radicalization
trajectory. These fifteen cases aim to achieve maximum variance in regard to the role the Internet
played in radicalization processes across individuals. All cases are from open sources, all are
relevant to Canada although some cases selected include individuals active in (or coming from)
other countries. The aim is to provide a clear assessment of the aspects of the literature from the
research field of the social psychology of the Internet that has been shown most relevant to violent
extremism.

The second part of the report builds off the literature review and case study analysis, looking
at programs that aim to counter violent extremism online. This section can be broken down
into two sub-sections. First a review of the literature on countering violent extremism online is