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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Detalles Bibliográficos
Autor principal: Semmelbeck, Julia (Autor)
Otros Autores: Besaw, Clayton
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2020
En: Journal of quantitative criminology
Año: 2020, Volumen: 36, Número: 3, Páginas: 527-558
Acceso en línea: Volltext (Resolving-System)
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Palabras clave:
Machine learning
Organized Crime
Organized crime
Terrorism
machine learning
Descripción
Sumario: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