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VOX-Pol Blog post.

VOX-Pol Blog post.

This report examines the patchwork of online text‑based instant messaging applications preferred by jihadist and far‑right extremist groups, with a focus on charting their technical affordances and their host companies’ stances on user privacy, security and regulation. To this end, the report analyses six online messaging services (BCM, Gab Chat, Hoop Messenger, Riot.im, Rocket.Chat and TamTam) that have been or may be used in conjunction with Telegram by extremist groups.

Blogs, often treated as the equivalence of online personal diaries, have become one of the fastest growing types of Web-based media. Everyone is free to express their opinions and emotions very easily through blogs. In the blogosphere, many communities have emerged, which include hate groups and racists that are trying to share their ideology, express their views, or recruit new group members. It is important to analyse these virtual communities, defined based on membership and subscription linkages, in order to monitor for activities that are potentially harmful to society. While many Web mining and network analysis techniques have been used to analyze the content and structure of the Web sites of hate groups on the Internet, these techniques have not been applied to the study of hate groups in blogs. To address this issue, we have proposed a semi-automated approach in this research. The proposed approach consists of four modules, namely blog spider, information extraction, network analysis, and visualization. We applied this approach to identify and analyze a selected set of 28 anti-Blacks hate groups (820 bloggers) on Xanga, one of the most popular blog hosting sites. Our analysis results revealed some interesting demographical and topological characteristics in these groups, and identified at least two large communities on top of the smaller ones. The study also demonstrated the feasibility in applying the proposed approach in the study of hate groups and other related communities in blogs.

Extremism has been a problematic term to define and suggests different and opposing meanings. This study explores how Twitter users conceptualize extremism in Arabic and express their opinions/arguments to construct the term. A corpus of tweets was collected from Twitter API using the word ‘تطرف أو متطرف’ in Arabic for extremist/extremism. A topic modeling algorithm was then applied to the dataset to uncover latent associated concepts underlying extremism, followed by a critical discourse analysis using Van Dijk’s Sociocognitive approach. The discursive and linguistic strategies used by Twitter users to support and justify their views of extremism were examined. The findings demonstrate an ideological influence that controls the concept of extremism, keeping it open to manipulation to serve shared interests and goals. Arab users of Twitter use extremism to promote their groups’ positive schema against others-negative schema.

The emergence and actions of the so-called Islamic State
of Iraq and the Levant (ISIL/ISIS) has received widespread
news coverage across the World, largely due to their capture
of large swathes of land across Syria and Iraq, and the
publishing of execution and propaganda videos. Enticed by
such material published on social media and attracted to the
cause of ISIS, there have been numerous reports of individuals
from European countries (the United Kingdom and France
in particular) moving to Syria and joining ISIS. In this paper
our aim to understand what happens to Europe-based
Twitter users before, during, and after they exhibit pro-ISIS
behaviour (i.e. using pro-ISIS terms, sharing content from
pro-ISIS accounts), characterising such behaviour as radicalisation
signals. We adopt a data-mining oriented approach
to computationally determine time points of activation (i.e.
when users begin to adopt pro-ISIS behaviour), characterise
divergent behaviour (both lexically and socially), and quantify
influence dynamics as pro-ISIS terms are adopted. Our
findings show that: (i) of 154K users examined only 727 exhibited
signs of pro-ISIS behaviour and the vast majority of
those 727 users became activated with such behaviour during
the summer of 2014 when ISIS shared many beheading
videos online; (ii) users exhibit significant behaviour divergence
around the time of their activation, and; (iii) social homophily
has a strong bearing on the diffusion process of proISIS
terms through Twitter.