ABSTRACT
There is widespread recognition among scholars and practitioners that the counterteiTorism literature suffers from a lack of primary-source field research. This shortcoming is largely due to a failure to integrate ethnographic research into modeling efforts, as well as a failme more broadly to appreciate the significance of ethnographically valid data in human, social, cultural, and behavioral studies in a systematic investigation of adversarial behavior. The project briefly outlined in this preliminary paper seeks to redress this deficiency by combining the strengths of ethnographic field research (collected by social scientists at Penn State) with the sophisticated modeling capabilities of computer scientists (at Carnegie Mellon University). Specifically, we are analyzing data from interview transcripts, news reports, and other open sources concerning the radical Islamic group alMuhajiroun. Using competitive adaptation as a comparative organizational
framework, this project focuses on the process by which adversaries learn from each other in complex adaptive systems and tailor their activities to achieve their organizational goals in light of their opponents' actions. Ultimately, we will develop a meso-level model of terrorist networks that combines insights from organizational theory, psychology, network analysis, and computational modeling. This model will assist counterterrorism practitioners in their decision-making regarding the impact of specific interventions.
