Population Distribution, Neighborhood Networks, and Neighborhood Crime: A Simulation Study

John Hipp, University of California, Irvine
Carter Butts, University of California, Irvine
Nicholas Nagle, University of Tennessee
Ryan Acton, University of California, Irvine
Adam Boessen, University of California, Irvine

This study integrates literatures from demography, criminology, and the field of social networks. We create a spatial representation of the households in two cities (Cincinnati and Tucson) and simulate possible social networks between these residents based on known spatial interaction functions obtained in prior research. We then construct social network measures measuring the possibility of information flow, as well as cohesion. We combine these with information on the point location of crime to assess their relationship with crime rates aggregated to blocks, block groups, and tracts. We also test and find that population distribution measures capturing greater degrees of clustering are associated with areas with lower crime rates. We find that measures of cohesion also have a particularly strong negative effect on crime rates. It is notable that these effects are strongest when measuring these constructs at the smallest geographic unit of analysis—blocks.