Analyzing terrorist networks: a case study of the global salafi jihad network

  • Authors:

  • Jialun Qin;Jennifer J. Xu;Daning Hu;Marc Sageman;Hsinchun Chen

  • Affiliations:

  • Department of Management Information Systems, The University of Arizona, Tucson, AZ;Department of Management Information Systems, The University of Arizona, Tucson, AZ;Department of Management Information Systems, The University of Arizona, Tucson, AZ;The Solomon Asch Center For Study of Ethnopolitical Conflict, University of Pennsylvania, Philadelphia, PA;Department of Management Information Systems, The University of Arizona, Tucson, AZ

  • Venue:
  • ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
  • Year:
  • 2005

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Abstract

It is very important for us to understand the functions and structures of terrorist networks to win the battle against terror. However, previous studies of terrorist network structure have generated little actionable results. This is mainly due to the difficulty in collecting and accessing reliable data and the lack of advanced network analysis methodologies in the field. To address these problems, we employed several advance network analysis techniques ranging from social network analysis to Web structural mining on a Global Salafi Jihad network dataset collected through a large scale empirical study. Our study demonstrated the effectiveness and usefulness of advanced network techniques in terrorist network analysis domain. We also introduced the Web structural mining technique into the terrorist network analysis field which, to the best our knowledge, has never been used in this domain. More importantly, the results from our analysis provide not only insights for terrorism research community but also empirical implications that may help law-reinforcement, intelligence, and security communities to make our nation safer.