Abstract
Distinctive combinations of attributes and behaviors lead us to improve on existing representations of terrorist organizations within a space of group properties. We review and extend a four-step procedure that discovers (statistical) interaction effects among relevant variables based on clusters of organizations derived from group properties. Application of this procedure to 395 terrorist groups in the period 1998-2005 identifies distinctive patterns of unconventional weapons activity and improves prediction of the groups that use or pursue chemical, biological, radiological, or nuclear (CBRN) weapons.
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Melamed, D., Schoon, E., Breiger, R., Asal, V., Rethemeyer, R.K. (2012). Using Organizational Similarity to Identify Statistical Interactions for Improving Situational Awareness of CBRN Activities. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds) Social Computing, Behavioral - Cultural Modeling and Prediction. SBP 2012. Lecture Notes in Computer Science, vol 7227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29047-3_8
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DOI: https://doi.org/10.1007/978-3-642-29047-3_8
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