Spatial Network Effects on Neighborhood Violence and Overall Crime: A Computational Statistics Analysis of Employment-Based Econetworks

Corina Graif , Pennsylvania State University
Brittany Freelin, Pennsylvania State University
Yu-Hsuan Kuo, Pennsylvania State University
Hongjian Wang , Pennsylvania State University
Zhenhui Li, Pennsylvania State University
Daniel Kifer, Pennsylvania State University

Research on the neighborhood determinants of violence and overall crime has typically focused on internal or geographically proximate processes. However, a growing body of research shows that people often engage in interactions away from home areas, contributing to dynamic connections between places. The current study expands on emerging work to analyze interactions between places based on population mobility patterns measured through commuting flows across Chicago communities. It integrates standard demographic and spatial methods with machine learning and computational statistics approaches to investigate the extent to which neighborhood violence and overall crime depends not just on internal or surrounding disadvantage but also on the disadvantage of areas connected to it through commuting. The findings contribute to ecological theories of crime, neighborhood isolation, and network effects by showing that communities can influence each other from a distance and suggesting that connectivity to less disadvantaged employment hubs may decrease local crime.

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 Presented in Session 157. Violence and Health