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Detecting Criminal Networks Using Social Similarity

机译:使用社会相似性检测刑事网络

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Existing literature shows that social demographics features of criminal network members are important. Examples include similarity on kinship, coming from the same family, the same ethnic origin or hometown, and living in the same neighborhoods. This paper investigates whether these social similarity features can be used for detecting members of criminal networks. We developed XSDM (Extended Social Detection Model), which removes some of the weaknesses of its predecessor SODM (Social Detection Model) by adding the attribute of living in the same neighborhood in addition to having the same surname and coming from the same hometown. XSDM is tested on the Diyarbakir dataset, containing 221 drug dealing networks. XSDM detected 81 out of 221 drug dealing networks using social demographic features of individual criminals. XSDM is evaluated by recall and precision values which performed better its predecessor SODM.
机译:现有文学表明,刑事网络成员的社会人口统计学特征很重要。 例子包括亲属关系的相似性,来自同一个家庭,相同的民族或家乡,生活在同一个社区。 本文调查了这些社交相似性功能是否可用于检测刑事网络成员。 我们开发了XSDM(扩展社交检测模型),除了拥有相同的姓氏和来自同一姓氏并来自同一社区的生活中,可以通过添加居住在同一个社区的属性并来自同一个家乡。 XSDM在Diyarbakir DataSet上进行测试,包含221个药物处理网络。 XSDM使用个人罪犯的社会人群特征检测到221个药物交易网络中的81个。 XSDM由召回和精确值进行评估,该值更好地执行其前任SodM。

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