Identifying Regional Hotspots of Gun Violence in the United States Using DBSCAN Clustering

Abstract

This study utilizes the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to analyze and map the geographical distribution of gun violence across the United States, drawing on data sourced from the Gun Violence Archive. By identifying distinct clusters of gun violence incidents, the research highlights significant spatial patterns and hotspots, particularly in major urban centers such as Los Angeles, Phoenix, Chicago, and New York. These findings underscore the correlation between gun violence and urban density, socio-economic factors, and the distribution of firearm accessibility. The study also discusses the implications of these spatial patterns for public safety and legal frameworks, advocating for targeted policy interventions and resource allocation to areas most affected by gun violence. Additionally, the research addresses the limitations of the current dataset and the DBSCAN method, proposing future research directions that incorporate a broader range of data sources and advanced analytical techniques. This paper aims to provide policymakers and law enforcement agencies with actionable insights to develop more effective gun control measures and violence prevention strategies.