GANGNET · Modelling the dynamics of Violent Gang-Crime: a Network approach
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2021-10-01 → 2024-02-28
- EU contribution
- €212,934
- Participants
- 1
- Scheme
- MSCA-IF
Lines connect the coordinator with its partners.
Results in brief
Modelling the dynamics of Violent Gang-Crime: a Network approach
Gang delinquency is one of the rising challenges to the security of urban environments and the wellbeing of European communities. Among the negative externalities generated by gangs’ activity, the propagation of inter-group violent behaviours inflicts a heavy toll on citizens in terms of violence and increased insecurity. The goal of GANGNeT is to study the propagation of criminal behaviours along groups of co-offenders. Society is made of relations, and so are criminal phenomena. However, while connections might lead to positive outcomes, they can also foster the spread and continuation of violent and illegal activities. This key aspect in the study of crime is largely unexplored. This is due to (a) lack of data and, crucially, (b) statistical complexity of modelling highly dynamical processes involving hundreds of goal-driven individuals. The key innovation of GANGNeT is in implementation of new mixed methods from network science, economics and advanced computational techniques to link and explain two seemingly distant sub-issues: (a) the evolution of complex and highly-dynamic relational networks of incentive-driven co-offenders (b) the propagation of persistent intergroup victimization. GANGNeT has two specific goals: (I)The development of a novel mathematical model to explain how violence propagates on co-offending networks. The model is used to construct an early-signal indicator for violence out-breaks across organized crime groups and aims to be a platform for further empirical and theoretical analysis. (II) Empirical analysis of a new, surprisingly rich crime dataset to: (II.1) explain the interplay between violence and drug dealing in the behaviour of organized crime groups. (II.2) calibrate the model in (I) for predictive policing forecasting of OCG violence.
Data: CORDIS, © European Union
Project objective
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
Original text from CORDIS.
Participants
- THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE · CAMBRIDGECoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union