To Blend in or Hide Out? A Network Analysis on Maritime Criminal Co-voyages in Taiwan

ObjectivesUnderstanding how covert networks are formed is key to disrupting the operation of illicit activities. Applying standard network measures to a covert network, while useful, is limited in identifying the peculiar properties of the network in question. It is important that we compare the cov...

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Bibliographische Detailangaben
1. VerfasserIn: Jiang, Yansheng (VerfasserIn)
Beteiligte: Chang, Yi-chun 1932- (VerfasserIn) ; Weng, Wei
Medienart: Elektronisch Aufsatz
Sprache:Englisch
Veröffentlicht: 2024
In: Journal of quantitative criminology
Jahr: 2024, Band: 40, Heft: 2, Seiten: 373-393
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Schlagwörter:
Bootstrap resampling
Co-voyage
Complex Networks
Crime and Technology
Illicit Trade and Treasure Hunting
Illicit networks
Maritime crime
Network clustering
Network homophily
Network topology
Organized Crime
Security
Transnational Crime
Beschreibung
Zusammenfassung:ObjectivesUnderstanding how covert networks are formed is key to disrupting the operation of illicit activities. Applying standard network measures to a covert network, while useful, is limited in identifying the peculiar properties of the network in question. It is important that we compare the covert network against a benchmark, be it random networks or, more ideally, the counterpart (overt) network in the same context. We report a study in collaboration with law enforcement agency to examine the co-voyage network of criminals and non-criminals. A comparison of the two groups of actors in their network positions allows us to test whether criminals tend to blend in or hide out from the population of non-criminals.MethodsDrawing on data on maritime activities in Taiwan recorded from years 2016 to 2018, we map a maritime co-voyage network of 53,009 nodes and 2,592,288 weighted links. We follow a bootstrap resampling procedure to estimate the structural features of the co-voyage networks of criminals and non-criminals.ResultsCriminals are more likely to co-voyage with their own type than non-criminals. Similarly, criminals are more clustered in the co-voyage network than non-criminals.ConclusionsIt is more supported that criminals segregate from than blend in non-criminals in the co-voyage network.
ISSN:1573-7799
DOI:10.1007/s10940-023-09572-1