Collecting and analyzing the presence of terrorists on the web: a case study of jihad websites

  • Authors:
  • Edna Reid;Jialun Qin;Yilu Zhou;Guanpi Lai;Marc Sageman;Gabriel Weimann;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;Department of Systems and Industry Engineering, The University of Arizona, Tucson, AZ;The Solomon Asch Center For Study of Ethnopolitical Conflict, University of Pennsylvania, Philadelphia, PA;Department of Communication, Haifa University, Haifa, Israel;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

The Internet which has enabled global businesses to flourish has become the very same channel for mushrooming ‘terrorist news networks.' Terrorist organizations and their sympathizers have found a cost-effective resource to advance their courses by posting high-impact Websites with short shelf-lives. Because of their evanescent nature, terrorism research communities require unrestrained access to digitally archived Websites to mine their contents and pursue various types of analyses. However, organizations that specialize in capturing, archiving, and analyzing Jihad terrorist Websites employ different, manualbased analyses techniques that are inefficient and not scalable. This study proposes the development of automated or semi-automated procedures and systematic methodologies for capturing Jihad terrorist Website data and its subsequent analyses. By analyzing the content of hyperlinked terrorist Websites and constructing visual social network maps, our study is able to generate an integrated approach to the study of Jihad terrorism, their network structure, component clusters, and cluster affinity.