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sociogeNEsis of criMinal nEtworks: reconStruction, dIscovery and diSruption

Project description

Innovative statistical methods to study modern criminal networks

Europol views criminal networks as contemporary equivalents of the Hydra from Greek mythology, characterised by enigmatic origins, flexible structures, and multifaceted evolutions. The ERC-funded NEMESIS project is taking a novel approach to tackling the challenges of uncovering, reconstructing, and disrupting these modern criminal networks. It focuses on transforming the main obstacles, which are data incompleteness and complexity, into valuable resources. By integrating social sciences and statistics, the project aims to enhance our understanding of these criminal networks as well as the public policies related to them. To accomplish this goal, NEMESIS will develop and employ innovative statistical concepts to model criminal networks, revolutionising their analysis and disruption while also paving the way for new resources, theories, strategies, and policies.

Objective

Europol defines criminal networks as a modern version of the Hydra mythological creature, with obscure genesis, fluid structure and multifaceted evolutions. Leveraging a unique synergy between Social Sciences and Statistics, NEMESIS departs from current practice to translate the main obstacles (i.e. data incompleteness and complexity) underlying the reconstruction, discovery and disruption of these modern criminal networks into a unique resource for crucially expanding available knowledge and policies. This ambitious perspective builds on three somewhat overlooked, yet fundamental, observations. First, data missingness in criminal networks can be, in fact, a fundamental source of information on the structure and secrecy strategies of organized crime, and, as such, should be embraced and not disregarded for network reconstruction. Second, the complexity and multiplexity of covert and overt interactions among criminals may hide a wealth of yet unexplored knowledge on the formation, mutation and sociogenesis of criminal networks, hence invaluable for their discovery. Third, “cutting” Hydra heads without realistic predictions of the corresponding re-generation processes undermines not only the development of innovative law-enforcement disruption strategies, but also the identification of more nuanced high-value targets. NEMESIS transforms these perspectives into rigorous, interpretable and practically-impactful generative statistical models of criminal networks and introduces innovative concepts of secret criminal species, covert networking activity codes and dark evolutionary trees. This perspective is expected to revolutionize current practice of conceptualizing, reconstructing, analyzing and disrupting criminal networks, while opening new avenues for the creation of frontier data-related resources, social theories, law-enforcement strategies and public policies.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2023-STG

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Host institution

UNIVERSITA COMMERCIALE LUIGI BOCCONI
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 498 794,00
Address
VIA SARFATTI 25
20136 Milano
Italy

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Region
Nord-Ovest Lombardia Milano
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 498 794,00

Beneficiaries (1)

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