Online Library

The growing use of the Internet as a major means of communication has led to the formation of cyber-communities, which have become increasingly appealing to violent extremists due to the unregulated nature of Internet communication. Online communities enable violent extremists to increase recruitment by allowing them to build personal relationships with a worldwide audience capable of accessing uncensored content. This research presents methods for identifying and forecasting the recruitment activities of violent groups within extremist social media websites. Specifically, these methods employ techniques within supervised learning and natural language processing for automatically: (1) identifying forum posts intended to recruit new violent extremist members, and (2) forecasting recruitment efforts by tracking changes in an online community’s discussion over time. We used data from the western jihadist website Ansar AlJihad Network, which was compiled by the University of Arizona’s Dark Web Project. Multiple judges manually annotated a sample of these data, marking 192 randomly sampled posts as recruiting (Yes) or non-recruiting (No). We observed significant agreement between the judges’ labels; the confidence interval of Cohen’s kappa was (0.5,0.9) at p=0.01. We used naive Bayes models, logistic regression, classification trees, boosting, and support vector machines (SVM) to classify the forum posts in a 10-fold cross-validation experimental setup. Evaluation with receiver operating characteristic (ROC) curves show that our SVM classifier achieves 89% area under the curve (AUC), a significant improvement over the 63% AUC performance achieved by our simplest naive Bayes model (Tukey’s test at p=0.05). The forecasting task uses a time series regression analysis to model the daily count of extremist recruitment posts. Evaluation with mean absolute scaled error (MASE) shows that employing latent topics as predictors can reduce forecast error compared to a naive (random-walk) model and the baseline time series model. To our knowledge, these are the first results reported on these tasks, and our analysis indicates that automatic detection and forecasting of online terrorist recruitment are feasible tasks. This research could ultimately help identify the impact of violent organizations, like terrorist groups, within the social network of an online community. There are also a number of important areas of future work including classifying non-English posts and measuring how recruitment posts and current events change membership numbers over time.

The current foreign fighter problem has received significant global media attention. Why and how do individuals from relatively affluent Western countries travel to poor and war torn countries to fight in a foreign war? How do social media and the internet impact the process? Ultimately, fighting in a foreign war requires the will and ability to participate, which in turn requires that an individual overcome significant psychological and physical barriers. The process of overcoming these participation barriers and thus the process of becoming a foreign fighter, hinges on four key factors: transnational ideology, close-knit social groups, and transnational resource networks, and a foreign sponsor facilitates the process by integrating the other three factors. Prior to social media and the internet, this process worked through local networks with face-to-face interaction. With the spread of social media and the internet, these networks and interactions have become increasingly global and virtual, increasing audience numbers but also increasing state ability to intervene. Analyzing globalization’s impact, including what has changed and what has stayed the same, is important to understanding the foreign fighter phenomenon both now and in the future.

On how participation via Internet and social media transform cultural production

The attacks suffered by France in January and November 2015, and then in the course of 2016, especially the Nice attack, provoked intense online activity both during the events and in the months that followed. The digital traces left by this reactivity and reactions to events gave rise, from the very first days and even hours after the attacks, to a ‘real-time’ institutional archiving by the National Library of France (Bibliothèque nationale de France) and the National Audio-visual Institute (Institut national de l’audiovisuel). The results amount to millions of archived tweets and URLs. This article seeks to highlight some of the most significant issues raised by these relatively unprecedented corpora, from collection to exploitation, from online stream of data to its mediation and re-composition. Indeed, web archiving practices in times of emergency and crises are significant, almost emblematic, loci to explore the human and technical agencies, and the complex temporalities, of ‘born-digital’ heritage. The cases examined here emphasize the way these ‘emergency collections’ challenge the perimeters and the very nature of web archives as part of our digital and societal heritage, and the guiding visions of its governance and mission. Finally, the present analysis underlines the need for a careful contextualization of the design process – both of original web pages or tweets and of their archived images – and of the tools deployed to collect, retrieve and analyse them.

VOX-Pol Blog Post.

VOX-Pol Blog post.