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dc.contributor.authorGollini, Isabellaen
dc.contributor.authorCaimo, Albertoen
dc.contributor.authorCampana, Paoloen
dc.date.accessioned2020-07-09T23:30:19Z
dc.date.available2020-07-09T23:30:19Z
dc.identifier.issn0378-8733
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/307817
dc.description.abstractIllegal 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.
dc.publisherREDES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleModelling interactions among offenders: A latent space approach for interdependent ego-networksen
dc.typeArticle
prism.publicationNameSocial Networksen
dc.identifier.doi10.17863/CAM.54911
dcterms.dateAccepted2020-07-03en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020-07-03en
dc.contributor.orcidCampana, Paolo [0000-0003-2448-9130]
rioxxterms.typeJournal Article/Reviewen
cam.orpheus.counter32*
rioxxterms.freetoread.startdate2023-07-09


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's licence is described as Attribution-NonCommercial-NoDerivatives 4.0 International