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A temporal analysis of crime concentrations in micro-places and the ambient population
Thu, September 12, 1:00 to 2:15pm, Faculty of Law, University of Bucharest, Floor: 1st floor, Room 2.06Abstract
The present study examines the temporal concentration of different crime types in Ghent, Belgium, between 2007-2018. Police-registered data on residential burglary, aggressive theft, battery incidents, car theft, theft out of car and bicycle theft are used to explore daily and weekly crime cycles by constructing crime heartbeats (Prieto Curiel, 2023) to detect moments with higher and lower intensity of crime events. In doing so, this study not only analyses temporal crime concentration city-wide, but also investigates daily and weekly crime cycles and concentration at the micro-geographic level, specifically at the grid level (using a grid of 200 by 200 meters). Furthermore, this study also explores the relationship between weekly crime concentrations and the ambient population over a three month period. The ambient population, representing the number of individuals present in a given area at a specific time, serves as a dynamic measure of population and population (im)mobility, encompassing crowd and footfall dynamics. The ambient population is estimated using mobile phone data consisting of counts of the number of present phones per hour for each cell of the grid during a period of three months in 2018 (N = 595,858,852 raw data points). Correlation and regression-based analyses are conducted to analyze the relationship between temporal crime concentrations and the ambient population at microgeographic units over a three-month period. The implications of the findings are multifaceted and may impact future research on big data policing, policy formulation, and practical applications of spatiotemporal crime analysis in urban contexts.