2019
DOI: 10.17863/cam.41581
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"I heard it through the grapevine": A Randomized Controlled Trial on the Direct and Vicarious Effects of Preventative Specific Deterrence Initiatives in Criminal Networks

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Cited by 2 publications
(1 citation statement)
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“…Example SNA applications include: Campana and Giovannetti (2020) use a network-based approach for prediction, using information on previous violent acts, possession of weapons, and that of associates also, to predict violent attacks with injury; Grassi et al (2019) use various centrality measures to assess leaders in criminal networks (Italian mafia), with significant brokerage values indicating they favored face-to-face meetings rather than telephone use with the danger of wiretaps (Calderoni & Superchi, 2019); Ariel et al (2019) use SNA to identify prolific offenders and subsequently conducted a randomized controlled trial to measure the effect of a "specific deterrence" message on prolific offenders and their co-offenders; Bright et al (2019) employed a longitudinal analysis to investigate structural and functional changes in an Australian drug trafficking network over time; Crocker et al (2019) investigate the structure of persistent theft and shop theft gangs using SNA; Ünal (2019) explores the balance between security and efficiency in terrorism and criminal networks with SNA measures such as path length and clustering of sub-groups; and finally, Lim et al (2019) use deep reinforcement learning to infer missing nodes and links in incomplete and inconsistent criminal activities data.…”
Section: Sna Link Analysismentioning
confidence: 99%
“…Example SNA applications include: Campana and Giovannetti (2020) use a network-based approach for prediction, using information on previous violent acts, possession of weapons, and that of associates also, to predict violent attacks with injury; Grassi et al (2019) use various centrality measures to assess leaders in criminal networks (Italian mafia), with significant brokerage values indicating they favored face-to-face meetings rather than telephone use with the danger of wiretaps (Calderoni & Superchi, 2019); Ariel et al (2019) use SNA to identify prolific offenders and subsequently conducted a randomized controlled trial to measure the effect of a "specific deterrence" message on prolific offenders and their co-offenders; Bright et al (2019) employed a longitudinal analysis to investigate structural and functional changes in an Australian drug trafficking network over time; Crocker et al (2019) investigate the structure of persistent theft and shop theft gangs using SNA; Ünal (2019) explores the balance between security and efficiency in terrorism and criminal networks with SNA measures such as path length and clustering of sub-groups; and finally, Lim et al (2019) use deep reinforcement learning to infer missing nodes and links in incomplete and inconsistent criminal activities data.…”
Section: Sna Link Analysismentioning
confidence: 99%