Using organizational similarity to identify statistical interactions for improving situational awareness of CBRN activities

David Melamed, Eric Schoon, Ronald Breiger, Victor Asal, R. Karl Rethemeyer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationSocial Computing, Behavioral-Cultural Modeling and Prediction, 5th International Conference, SBP 2012, Proceedings
Pages61-68
Number of pages8
DOIs
StatePublished - 2012
Event5th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2012 - College Park, MD, United States
Duration: Apr 3 2012Apr 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7227 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2012
Country/TerritoryUnited States
CityCollege Park, MD
Period4/3/124/5/12

Keywords

  • CBRN use or pursuit
  • profiling
  • regression modeling
  • terrorism

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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