Modelling the dynamics of Violent Gang Crime a Network approach
GANGNET is a project motivated by two intertwined emergencies of contemporary EU urban landscape: (1) the emergence of stable co-offending groups (2) the rapid propagation of inter-group violence (e.g. knife epidemics in UK). The...
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Información proyecto GANGNET
Duración del proyecto: 34 meses
Fecha Inicio: 2021-04-08
Fecha Fin: 2024-02-28
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Descripción del proyecto
GANGNET is a project motivated by two intertwined emergencies of contemporary EU urban landscape: (1) the emergence of stable co-offending groups (2) the rapid propagation of inter-group violence (e.g. knife epidemics in UK). The key of my research is the use of innovative techniques from network theory and computational methods to inform regulators with better gang-crime risk prediction and more effective containment strategies.
Relational networks are recognized as drivers of individual’s criminal activity: criminal groups are both organizations as well as social environments. For members of co-offending groups, interaction is both at group-level and at inter-group level. At the current state of art, little is known about the channel by which inter-personal links affect inter-group dynamics and trigger systemic phenomena. Therefore, it is unclear what individual-level factors EU policy-makers should monitor to control systemic urgencies such as the outbreak of group violence epidemics or formation of criminal alliances. Regulators contain crime via offender or groups-focused devices. However, as offenders and groups act within endogenous networks, unintended consequences such as increased inter-gang instability and violence can emerge as the result of spurious containment attempts.
The project uncovers the theoretical and empirical structure of gang dynamics by adopting a network perspective. The goal is to understand how individuals act upon the influence of a stratified social network and to what extent isolated behaviour from single individuals can trigger inter-group system-wide dynamics. The project is developed along three directions aiming to understand how: (1) interaction between incentive-driven offenders determine group-level activities (2) group-level activities can lead to systemically relevant phenomena that unfold through relational networks (3) develop synthetic metrics to measure effectiveness of individual or group based containment policies