Measuring the colocation of crime hotspots

Abstract Crimes tend to concentrate in high-risk places known as crime hotspots. While the size and locations of such hotspots vary between different types would underlying conditions that trigger each crime, extent overlaps their is understudied. Using data from Chicago aggregated at community-area census-tract levels, this paper investigates patterns overlapping see whether a specific group regularly form joint cluster. Specifically, we identify statistically significant for and, using frequent-pattern-growth algorithm, analyse frequency combination crimes sharing hotspot across study area. Results suggest stable multi-layered colocations area holds its subset: namely, pervasive, primary consisting assault , battery criminal damage property which are frequently joined by 7 additional (e.g. street robbery motor vehicle theft weapons violation ) comprise secondary colocations, some evolving an even larger, tertiary colocation with up 11 homicide, sexual assault, narcotics crime-riddled neighbourhoods. This structure well diagrams show most representative improve our understanding association indicators other crimes.