Modelling interactions among offenders: A latent space approach for interdependent ego-networks
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Journal Title
Social Networks
ISSN
0378-8733
Publisher
REDES
Type
Article
This Version
AM
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Gollini, I., Caimo, A., & Campana, P. Modelling interactions among offenders: A latent space approach for interdependent ego-networks. Social Networks https://doi.org/10.17863/CAM.54911
Abstract
Illegal markets are notoriously difficult to study. Police data offer an increasingly exploited source of evidence. However, their secondary nature poses challenges for researchers. A key issue is that researchers often have to deal with two sets of actors: targeted and non-targeted. This work develops a latent space model for interdependent ego-networks purposely created to deal with the targeted nature of police evidence. By treating targeted offenders as egos and their contacts as alters, the model (a) leverages on the full information available and (b) mirrors the specificity of the data collection strategy. The paper then applies this approach to analyse a real-world example of illegal markets, namely the smuggling of migrants. To this end, we utilise a novel dataset of 21,555 phone conversations wiretapped by the police to study interactions among offenders.
Embargo Lift Date
2023-07-09
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.54911
This record's URL: https://www.repository.cam.ac.uk/handle/1810/307817
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: https://creativecommons.org/licenses/by-nc-nd/4.0/