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Identifying criminal organizations from their social network structures

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dc.contributor.author Çınar, Muhammet Serkan
dc.contributor.author Genç, Burkay
dc.contributor.author Sever, Hayri
dc.date.accessioned 2020-01-29T12:07:48Z
dc.date.available 2020-01-29T12:07:48Z
dc.date.issued 2019
dc.identifier.citation Cinar, Muhammet Serkan; Genc, Burkay; Sever, Hayri, "Identifying criminal organizations from their social network structures", Identifying criminal organizations from their social network structures, Vol. 27, No. 1, pp. 421-436, (2019). tr_TR
dc.identifier.issn 1300-0632
dc.identifier.uri http://hdl.handle.net/20.500.12416/2380
dc.description.abstract Identification of criminal structures within very large social networks is an essential security feat. By identifying such structures, it may be possible to track, neutralize, and terminate the corresponding criminal organizations before they act. We evaluate the effectiveness of three different methods for classifying an unknown network as terrorist, cocaine, or noncriminal. We consider three methods for the identification of network types: evaluating common social network analysis metrics, modeling with a decision tree, and network motif frequency analysis. The empirical results show that these three methods can provide significant improvements in distinguishing all three network types. We show that these methods are viable enough to be used as supporting evidence by security forces in their fight against criminal organizations operating on social networks. tr_TR
dc.language.iso eng tr_TR
dc.publisher Tubitak Scientific & Technical Research Council Turkey tr_TR
dc.relation.isversionof 10.3906/elk-1806-52 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.subject Criminal Networks tr_TR
dc.subject Identification tr_TR
dc.subject Decision Tree tr_TR
dc.subject Motif Analysis tr_TR
dc.subject Machine Learning tr_TR
dc.title Identifying criminal organizations from their social network structures tr_TR
dc.type article tr_TR
dc.relation.journal Turkish Journal of Electrical Engineering and Computer Sciences tr_TR
dc.contributor.authorID 11916 tr_TR
dc.identifier.volume 27 tr_TR
dc.identifier.issue 1 tr_TR
dc.identifier.startpage 421 tr_TR
dc.identifier.endpage 436 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Yazılım Mühendisliği Bölümü tr_TR


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