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With the rise of the Islamic State (IS), a great deal of attention has recently been drawn to two issues that have come to be seen as intricately linked: the role of women within pro-jihadist networks (Lahoud 2014; Hoyle, Bradford and Frenett 2015; Saltman and Smith 2015) and the use of social media as an indoctrination and recruitment tool by terrorist organizations (Weimann 2008; Bloom 2013; Klausen 2015). The present working paper is an attempt at improving our understanding of women’s participation in online jihadist networks through examination of the nature and scope of their activities within pro-IS and pro-AQ Twitter networks. To explore that participation, we look at women’s activities online through two different methodological lenses: a. by looking at gender in relation to female tweeting patterns; and b. by examining the content of women’s posts within and across two distinct pro-jihadist networks, one associated with IS, and the other comprised of women from various al-Qaeda (AQ)-affiliated groups.

VOX-Pol Blog post.

There can be few greater fears for a parent than their child being contacted by a stranger, indoctrinated with an extreme ideology, and encouraged to join a violent movement, all while accessing the internet from their bedroom. Children’s smartphones and computers
may be portals to the most dangerous places on earth. The use of the internet, and more specifically social media, by violent extremists is certainly nothing new. The technical skills and proficiency displayed by groups such as ISIS have been causing concern for governments, law enforcement, industry, schools, religious leaders, and parents around the world. In reality the radicalization of children is rare and particularly nuanced, and far from a linear process that exclusively occurs online. While the media have reported high-profile cases, such as the teenagers from Chicago who tried to leave the United States and join ISIS or the three girls from the United Kingdom who traveled through Turkey to Syria the frequency and nature of conversion to violent extremism is a lot more complex than often reported. Evidence from search histories, online interactions and social media profiles suggest that contact is being made by those intent on radicalizing others. However, while information can be sought and contact can be initiated, complete conversion to a violent ideology is not happening in isolation online. That is to say that the internet is serving as a facilitator, not a direct means of recruitment. In any case action needs to be taken to safeguard children and young people from these risks.

Common approaches to text categorization essentially rely either on n-gram counts or on word embeddings. This presents important difficulties in highly dynamic or quickly-interacting environments, where the appearance of new words and/or varied misspellings is the norm. A paradigmatic example of this situation is abusive online behavior, with social networks and media platforms struggling to effectively combat uncommon or nonblacklisted hate words. To better deal with these issues in those fast-paced environments, we propose using the error signal
of class-based language models as input to text classification algorithms. In particular, we train a next-character prediction model for any given class, and then exploit the error of such class-based models.
to inform a neural network classifier. This
way, we shift from the ability to describe
seen documents to the ability to predict
unseen content. Preliminary studies using out-of-vocabulary splits from abusive
tweet data show promising results, outperforming competitive text categorization
strategies by 4–11%.

The rise of technology has brought with it many benefits but also the potential for great dangers. In particular, Information Communication Technology (ICT) is involved in many facets of life-influencing systems, which range from power plants to airports. Terrorists are now realising the great possibilities of interfering with critical infrastructure. Remote access, reduced costs, automation, replication, speed, direct effect, varied targets and anonymity are all benefits that make attacking computers and networks in cyberspace an attractive solution. ICT could thus serve as a powerful instrument to advance political and ideological viewpoints. The ICT landscape now faces an emerging threat in the form of cyberterrorists. However, it is important not to incorrectly perceive ordinary cyber attacks as cyberterrorism. Cyberterrorism is different from cybercrime in that is has differing motives, attack goals, techniques and intended effects. The motivation for cyberterrorism largely stems from political and ideological views (religious, social activism, retributional). Cyber attacks are mainly driven by financial theft, fraud or espionage, whereas cyberterrorism aims to create publicity for a cause and leave a high impact. In this study, a Cyberterrorism Life Cycle (CLC) Model is developed in order to demonstrate the various factors that lead to the establishment and growth of cyberterrorism. The model depicts the various strategic and technical issues that are relevant to the field. Overall, this model aims to structure the dynamic interaction of the behavioural and technological factors that influence the development of cyberterrorism. Throughout the research, various factors that are influential to cyberterrorism are investigated. The research follows a systematic approach of revealing various underlying issues and thereafter compiling the holistic CLC model to depict these critical issues. Part 1 introduces cyberterrorism and provides the background to the field by discussing incidents and example groups. Initially, the concept of cyberterrorism is explored and the proposed definition tested. Part 2 looks at investigating cyberterrorism more deeply. A conceptual framework is presented that introduces the most pertinent factors in the field of cyberterrorism. Next, the traditional and innovative use of the Internet to carry out and support terrorism is explored. Then, the study addresses the determination of additional social factors using Partial Least Squares Path Modelling. In Part 3, the field of cyberterrorism is more intensely studied. Cyberterrorism is mapped to the Observe-Orient- Decide-Act (OODA) loop, which will form the basis of the CLC model. Thereafter, the most influential concepts essential to the field of cyberterrorism are applied in order to classify attacks as cyberterrorism using ontologies. Furthermore, in Part 3, countermeasures are discussed to look at ways to combat cyberterrorism. Part 4 forms the crux of the research. The CLC model is presented as a structured representation of the various influential factors relevant to cyberterrorism. Thereafter, the CLC model is simulated to show the field more dynamically. Overall, the CLC model presented in this study aims to show the interaction of the various strategic, behavioural and technical issues. The CLC model can help elucidate the reasons for attraction into extremist groups and how attacks are carried out.

This research analyses cloaked Facebook pages that are created to spread political propaganda by cloaking a user profile and imitating the identity of a political opponent in order to spark hateful and aggressive reactions. This inquiry is pursued through a multi-sited online ethnographic case study of Danish Facebook pages disguised as radical Islamist pages, which provoked racist and anti-Muslim reactions as well as negative sentiments towards refugees and immigrants in Denmark in general. Drawing on Jessie Daniels’ critical insights into cloaked websites, this research furthermore analyses the epistemological, methodological and conceptual challenges of online propaganda. It enhances our understanding of disinformation and propaganda in an increasingly interactive social media environment and contributes to a critical inquiry into social media and subversive politics.