Social network analysis as a tool for criminal intelligence: understanding its potential from the perspectives of intelligence analysts

Over the past two decades an increasing number of researchers have applied social network analysis (SNA) to various ‘dark’ networks. This research suggests that SNA is capable of revealing significant insights into the dynamics of dark networks, particularly the identification of critical nodes, whi...

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Bibliographische Detailangaben
1. VerfasserIn: Burcher, Morgan (VerfasserIn)
Beteiligte: Whelan, Chad
Medienart: Elektronisch Aufsatz
Sprache:Englisch
Veröffentlicht: 24 May 2017
In: Trends in organized crime
Jahr: 2018, Band: 21, Heft: 3, Seiten: [278]-294
Online-Zugang: Volltext (Resolving-System)
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Schlagwörter:
Social Network Analysis
Criminal networks
Criminal network characteristics
Dark networks
Law enforcement organisational characteristics
Beschreibung
Zusammenfassung:Over the past two decades an increasing number of researchers have applied social network analysis (SNA) to various ‘dark’ networks. This research suggests that SNA is capable of revealing significant insights into the dynamics of dark networks, particularly the identification of critical nodes, which can then be targeted by law enforcement and security agencies for disruption. However, there has so far been very little research into whether and how law enforcement agencies can actually leverage SNA in an operational environment and in particular the challenges agencies face when attempting to apply various network analysis techniques to criminal networks. This papergoes some way towards addressing these issues by drawing on qualitative interviews with criminal intelligence analysts from two Australian state law enforcement agencies. The primary contribution of this paper is to call attention to the organisational characteristics of law enforcement agencies which, we argue, can influence the capacity of criminal intelligence analysts to successfully apply SNA as much as the often citied ‘characteristics of criminal networks’.
Beschreibung:Published: 24 May 2017
Literaturverzeichnis: Seite 292-294
ISSN:1936-4830
DOI:10.1007/s12117-017-9313-8