Citation

Atsa'am DD, Wario R, Okpo FE. J. Appl. Secur. Res. 2020; 15(3): 369-384.

Copyright

(Copyright © 2020, Informa - Taylor and Francis Group)

DOI

10.1080/19361610.2020.1769461

PMID

unavailable

Abstract

This study deployed the agglomerative hierarchical clustering technique on the Global Terrorism Database to develop a new way of categorizing terrorism. Four clusters were extracted, resulting in a new categorization of terrorism based on casualties and consequences. The subcategories include low-casualty, medium-consequence terror groups; medium-casualty, high-consequence terror groups; high-casualty, low-consequence terror groups; and higher-casualty, low-consequence terror groups. The connectedness, separation, and compactness of the four clusters were evaluated and the results were reasonably accurate. This new categorization has useful application in counterterrorism regarding proportionate budgeting of weaponry and other resources.

Language: en

Keywords

casualties and consequences; data mining; Global Terrorism Database; hierarchical clustering; terrorism categorization