Information Systems Frontiers

, Volume 20, Issue 5, pp 1053–1074 | Cite as

Multimode co-clustering for analyzing terrorist networks

  • Ahmed Aleroud
  • Aryya Gangopadhyay


The phenomenon of terrorism is deemed one of the fundamental challenges in national security. Creating defensive technologies to mitigate terrorist attacks requires a simultaneous investigation of contextual relationships among their various dimensions. We proposed and evaluated a graph-based methodology to analyze terrorist networks through co-clustering in a multimode basis. Since there are many heterogeneous relationships in terrorist networks depending on the dimensions used during analysis, we utilized the clustering indicators of the multimode structure discovered in bi- and multimode graphs. Objects and activities that co-occur during terrorist attacks are identified by applying conventional clustering on those indicators. The novelty of our method is in the incremental creation of the multimode structure using its bi-mode counterparts. Our approach is evaluated using these measures: clustering stability and association confidence. The experimental results yields encouraging results in terms of simultaneous clustering of heterogeneous objects in terrorist networks.


Multimode clustering Terrorist networks Singular value decomposition k-means Social network analysis 


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Computer Information SystemsYarmouk UniversityIrbidJordan
  2. 2.Department of Information SystemsUniversity of Maryland, Baltimore County (UMBC)BaltimoreUSA

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