One major challenge facing the intelligence and security community is monitoring online media for terrorist group communications. This study addresses the online anonymity problem by applying authorship analysis to English and Arabic extremist group Web forum messages. The study evaluates the performance impact of different feature categories and techniques across both languages. To enhance writing style identification, researchers incorporated a comprehensive list of online authorship features. Additionally, they created an Arabic language model by adopting specific features and techniques, including an elongation filter and a root-clustering algorithm, to handle challenging linguistic characteristics. A series of experiments indicated a high level of efficacy in the models. Finally, the authors compare the English and Arabic language models and messages to aid the research community's understanding of the dynamics of these groups' authorship tendencies.

This article is part of a special issue on Homeland Security.