Crime can occur in micro locations based on the usual patterns of where people travel. This study used measures of the street network to capture potential pathways of travel by persons, and whether this is related to crime. We created a social network measure of betweenness to capture the busiest streets, and tested how they were related to crime levels. We accounted for the population at origin and destination points to better assess the potential traffic at a location. We also measured the number of businesses at a destination of each potential trip to also better assess the potential volume of travelers. We used data on 300,000 street segments in the Southern California region, and found that busier streets have more crime. However, at very high volumes of traffic the amount of crime begins to decrease.
You can access the article by ex lab-member Dr. Young-an Kim and Dr. John R. Hipp in Journal of Quantitative Criminology entitled, “Pathways: Examining Street Network Configurations, Structural Characteristics and Spatial Crime Patterns in Street Segments.”