Summary
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.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101116718 |
| Start date: | 01-01-2024 |
| End date: | 31-12-2028 |
| Total budget - Public funding: | 1 498 794,00 Euro - 1 498 794,00 Euro |
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Original description
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.Status
SIGNEDCall topic
ERC-2023-STGUpdate Date
12-03-2024
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