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To stop the spread of firearm violence, policing agencies use databases like the National Integrated Ballistic Information Network (NIBIN) to link gun incidents together through ballistic evidence. Ballistic evidence gathered at firearm-involved crime scenes is entered into NIBIN; a NIBIN-lead is generated if the recovered evidence can be connected to evidence from another incident. Often, one incident is linked to several incidents, creating a network of connected cases. This study aims to examine clusters of NIBIN-lead evidence-linked firearm networks of NIBIN-lead-involved cases to explore the geographical reach and movement among clusters and the homogeneity or diversity of affected neighborhoods. The data include NIBIN leads (n=1051) collected from a large Midwestern city in the United States. Using social network analysis, characteristics of NIBIN lead evidence-linked firearm networks are identified and visualized into sociograms which are then geocoded into a geographic information system for spatial analysis. Exploratory spatial analysis is used to visualize and describe the spatial distributions of the NIBIN-lead evidence-linked firearm networks for spatial heterogeneity and spatial autocorrelation. Clusters are analyzed and compared to the communities they are connected with. Results explore the variation of characteristics of NIBIN-lead evidence-linked firearm networks and the communities they affect.