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A Policy-Oriented Agent-Based Model of Recruitment into Organized Crime

Authors: Gian Maria Campedelli; Francesco Calderoni; Mario Paolucci; Tommaso Comunale; Daniele Vilone; Federico Cecconi; Giulia Andrighetto;

A Policy-Oriented Agent-Based Model of Recruitment into Organized Crime

Abstract

Criminal organizations exploit their presence on territories and local communities to recruit new workforce in order to carry out their criminal activities and business. The ability to attract individuals is crucial for maintaining power and control over the territories in which these groups are settled. This study proposes the formalization, development and analysis of an agent-based model (ABM) that simulates a neighborhood of Palermo (Sicily) with the aim to understand the pathways that lead individuals to recruitment into organized crime groups (OCGs). Using empirical data on social, economic and criminal conditions of the area under analysis, we use a multi-layer network approach to simulate this scenario. As the final goal, we test different policies to counter recruitment into OCGs. These scenarios are based on two different dimensions of prevention and intervention: (i) primary and secondary socialization and (ii) law enforcement targeting strategies.

Country
Italy
Keywords

Social and Information Networks (cs.SI), FOS: Computer and information sciences, FOS: Physical sciences, Computer Science - Social and Information Networks, Social and Behavioral Sciences, Nonlinear Sciences - Chaotic Dynamics, bepress|Social and Behavioral Sciences|Sociology, SocArXiv|Social and Behavioral Sciences|Sociology, Crime, Law, and Deviance, Computer Science - Computers and Society, Organized Crime, Sociology, bepress|Social and Behavioral Sciences|Sociology|Criminology, Criminal organizations Disruption strategies Public Policy Criminal involvement Law enforcement, Computers and Society (cs.CY), bepress|Social and Behavioral Sciences, Computer Science - Multiagent Systems, SocArXiv|Social and Behavioral Sciences, Chaotic Dynamics (nlin.CD), SocArXiv|Social and Behavioral Sciences|Sociology|Crime, Law, and Deviance, Multiagent Systems (cs.MA)

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid