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 language | English |
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Title of host publication | 6th International Conference on Internet of Things, Big Data and Security, IoTBDS 2021 |
Subtitle of host publication | Proceedings |
Pages | 329 - 337 |
Volume | 2021 |
ISBN (Electronic) | 9789897585043 |
Publication status | Published - 23 Apr 2021 |
Event | 6th International Conference on Internet of Things, Big Data and Security - Virtual Duration: 23 Apr 2021 → 25 Apr 2021 |
Conference
Conference | 6th International Conference on Internet of Things, Big Data and Security |
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Abbreviated title | IoTBDS 2021 |
Period | 23/04/21 → 25/04/21 |