Crime and social environments: differences between misdemeanors and felonies

Abstract

Owing to the growing population density of urban areas, many people are being increasingly exposed to criminal activity. Increasing crime rates raise the risk of both physical and psychological injury to law-abiding citizens, creating anxiety. From the viewpoint of complex systems, crime prevention through data science can be a solution to such issues. However, previous studies have focused only on a single aspect of crime, ignoring the complex interplay between the various characteristics, which must be considered in the analysis to understand the dynamics underlying criminal activities. In this study, we examined 12 features that have been identified as important correlates of crime rates using state-level statistics from the USA. We found that the correlates of misdemeanors and felonies differ. The number of misdemeanors is strongly associated with the police precinct, whereas felony rates are strongly correlated with gun possession and happiness. To account for these results, we present a mechanistic model that commits the crime based on the motivation regarding the profit and the penalty of crimes. Our findings suggest that the countermeasures for misdemeanors should be treated differently from those for felonies.