Homicide Network Detection based on Social Network Analysis

Victor Chang, Yeqing Mou, Qianwen Xu, Harleen Kaur, Ben S.C. Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper aims to explore the use of social network analysis in identifying the most active suspects and possible crime gangs in the network. The homicide dataset provided by White & Rosenfeld is employed and both the victim network and suspects network are structured by the use of Rstudio. This paper finds that the criminal gang and group of victims in homicide cases could be investigated by conducting centrality analysis and detecting cliques in these two one-mode networks. Moreover, the same features of victims or suspects are significant indicators for distinguishing and discovering victim groups or criminal gangs. As suspects or victims with the same features will be gathered into the same community in the community analysis of SNA, it is more effective to identify victim groups or criminal gangs by analyzing their characteristics, so that crimes can be resolved more efficiently or even prevented. © 2021 by SCITEPRESS - Science and Technology Publications, Lda.
Original languageEnglish
Title of host publication6th International Conference on Internet of Things, Big Data and Security, IoTBDS 2021
Subtitle of host publicationProceedings
Pages329 - 337
Volume2021
ISBN (Electronic)9789897585043
Publication statusPublished - 23 Apr 2021
Event6th International Conference on Internet of Things, Big Data and Security - Virtual
Duration: 23 Apr 202125 Apr 2021

Conference

Conference6th International Conference on Internet of Things, Big Data and Security
Abbreviated titleIoTBDS 2021
Period23/04/2125/04/21

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