Exploring the Determinants of Crime-Terror Cooperation using Machine Learning

This study seeks to further strengthen extant knowledge regarding terrorist group involvement in organized criminal activity through two means. First, it measures a set of environmental and organizational characteristics for a sample of well-known terrorist organizations based on the crime-terror li...

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Bibliographic Details
Authors: Semmelbeck, Julia 1986- (Author) ; Besaw, Clayton (Author)
Format: Electronic Article
Language:English
Published: 2020
In: Journal of quantitative criminology
Year: 2020, Volume: 36, Issue: 3, Pages: 527-558
Online Access: Volltext (Resolving-System)
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Keywords:
machine learning
Organized Crime
Terrorism
Organized crime
Machine learning
Description
Summary:This study seeks to further strengthen extant knowledge regarding terrorist group involvement in organized criminal activity through two means. First, it measures a set of environmental and organizational characteristics for a sample of well-known terrorist organizations based on the crime-terror literature. Second, it illustrates the utility of inductive research designs for examining patterns in the criminal behavior of terrorist groups for theory building and the potential risk classification of new terrorist organizations in the future.
ISSN:1573-7799
DOI:10.1007/s10940-019-09421-0