Detecting Criminal Networks Using Social Similarity

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.