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This article offers a descriptive analysis of the propaganda activities of Al Qaeda in the Islamic Maghreb on Internet social media. It examines the group’s propaganda actions from its creation in 1998 until the end of 2015 and argues that the use of social media, Twitter in particular, has failed to offer any real remedy to its mediocre propaganda actions. During the period in which its Twitter profiles were active, the organization continued to manifest the same problems, including a shortage of qualified human resources and poor internal coordination, which had prevented it from engaging in efficient propaganda activity previously. The study of the social media experience of the group offers further evidence of the vulnerabilities of this Maghrebi jihadist organization.

The main purpose of this policy brief is to highlight the risks of radicalization by utilizing statistical analysis. The main question interrogated here is to determine the relation between the level of social reaction and ISIS’s attacks. These reactions are measured through Google Trends of news, web searches, and video ratings. Methodologically, Turkey, France, Belgium, the United Kingdom and Germany are picked as the sample countries. In order to derive consistent data from Google’s database, the keywords “Islamic State of Iraq and the Levant,” and its some acronyms such as ISIS, ISIL, Islamic State, and DAESH are utilized.

This analysis revealed that Internet media might function as a recognition tool for terrorist organizations considering the fact that following ISIS’s attacks, people of both the target country and other countries progressively search ISIS on Google. Thus, one way or another, ISIS gains reputation and takes the opportunity for radicalization. Furthermore, the level of these searches differs among the aforementioned countries due to specific reasons, which are elaborated in this policy brief.

Until today there have been no women in the core leadership of Al Qaeda (Al Qaeda al
Sulba). While the organization is frequently described as patriarchal and exclusive of
women, women are among its most fervent supporters. A significant recent development
in women’s participation in violent extremism has been the dissemination of radical
ideologies online as recruiters and propagandists. In particular, online female recruiters
shame men to enlist in jihad by demanding that they protect their sisters in Islam from
sexual trespass, particularly by male non-believers. In addition to propagandists, a new
generation of jihadi leaders is looking to women to ensure the survival of the
organization by devising new religious justifications that would allow women to
participate in violent jihadist activities. An ideological schism over women’s
participation in jihad reflects a generational shift within the movement as well as
differences between the core of Al Qaeda and its regional affiliates globally.

Advances in digital technologies have provided ample positive impacts to modern society; however, in addition to such benefits, these innovations have inadvertently created a new venue for criminal activity to generate.

Combating Violent Extremism and Radicalization in the Digital Era is an essential reference for the latest research on the utilization of online tools by terrorist organizations to communicate with and recruit potential extremists and examines effective countermeasures employed by law enforcement agencies to defend against such threats. Focusing on perspectives from the social and behavioral sciences, this book is a critical source for researchers, analysts, intelligence officers, and policy makers interested in preventive methods for online terrorist activities.

We present a machine learning framework that leverages a mixture of metadata, network, and temporal features to detect extremist users, and predict content adopters and interaction reciprocity in social media. We exploit a unique dataset containing millions of tweets generated by more than 25 thousand users who have been manually identified, reported, and suspended by Twitter due to their involvement with extremist campaigns. We also leverage millions of tweets generated by a random sample of 25 thousand regular users who were exposed to, or consumed, extremist content. We carry out three forecasting tasks, (i) to detect extremist users, (ii) to estimate whether regular users will adopt extremist content, and finally (iii) to predict whether users will reciprocate contacts initiated by extremists. All forecasting tasks are set up in two scenarios: a post hoc (time independent) prediction task on aggregated data, and a simulated real-time prediction task. The performance of our framework is extremely promising, yielding in the different forecasting scenarios up to 93% AUC for extremist user detection, up to 80% AUC for content adoption prediction, and finally up to 72% AUC for interaction reciprocity forecasting. We conclude by providing a thorough feature analysis that helps determine which are the emerging signals that provide predictive power in different scenarios.

This case study explores the convergence of white extremist political ideology with mainstream political ideology on the micro-blogging platform Twitter – a phenomenon termed “inter-ideological mingling”. Exploring the spread of white extremism in the digital environment can provide insight into the growth of hate groups in the physical environment. A sample of 4800 tweets was examined through hierarchical cluster analysis and textual analysis. Several pieces of evidence were found supporting inter-ideological mingling. Cluster analysis shows that extremist terms are not isolated from terms found in mainstream political discourse. Textual analysis of individual tweets provides evidence for five strategies of inter-ideological mingling: joining, blending, piggybacking, backstaging, and narrating.