Multimode co-clustering for analyzing terrorist networks

Ahmed Aleroud () and Aryya Gangopadhyay ()
Additional contact information
Ahmed Aleroud: Yarmouk University
Aryya Gangopadhyay: University of Maryland, Baltimore County (UMBC)

Information Systems Frontiers, 2018, vol. 20, issue 5, No 12, 1053-1074

Abstract: Abstract 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.

Keywords: Multimode clustering; Terrorist networks; Singular value decomposition; k-means; Social network analysis (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10796-016-9712-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:20:y:2018:i:5:d:10.1007_s10796-016-9712-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1007/s10796-016-9712-4

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().