An Innovation Model of Crime Mapping in Prevention and Suppression of Human Trafficking

Author: Suriyawong, Chaichana; Sinthupinyo, Sukree & Triukose, Sipat

Abstract: Traditional approaches to combating human trafficking in Thailand have long been constrained by fragmented data ecosystems and reactive policing strategies. This study introduces an Integrated Intelligence-Led Policing Model that systematically combines Social Network Analysis (SNA) with Geographic Information Systems (GIS) to address these structural limitations. Utilizing a rare and comprehensive dataset of 1,316 cases involving 2,908 suspects and 3,762 victims collected by the Royal Thai Police (2018–2022), the analysis uncovers the hidden spatial – social topology of trafficking networks. The findings reveal complex structural dependencies and previously unrecognized operational hubs in Bangkok, Samut Prakan, and Nonthaburi, which function as critical command nodes. These insights were translated into a data-driven prototype system designed to shift law-enforcement practice from passive investigation to proactive, precision suppression. Beyond advancing analytical capacity, the study establishes an empirical foundation for data-driven policy formulation and interagency collaboration across the ASEAN region. Operational deployment with ATPD officers verified that the SNA – GIS prototype is fully actionable, delivering immediate improvements in identifying key suspects and high-risk nodes, thereby strengthening Thailand’s real-world capacity to prevent and suppress trafficking networks.

Keywords: Social Network Analysis (SNA), geographic information system (GIS), data visualization, Machine Learning, data-driven policing, crime mapping, human trafficking