Date of Award

12-2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Engineering and Sciences

First Advisor

Ronaldo Menezes

Second Advisor

Carmelo J. A. Bastos-Filho

Third Advisor

Vanessa A. Edkins

Fourth Advisor

Shengzhi Zhang

Abstract

Crime is ubiquitous in cities but lacks a statistical characterization that could lead to uncovering its underlying mechanisms. Cities are, however, in a constant process of organization making difficult to analyze urban phenomena. Yet, to understand urbanization and its consequences, we need to approach cities as evolving processes, instead of static objects. With this perspective, we examined regularities in crime regarding its growth, structure, and dynamics. We developed frameworks to examine the spatial, temporal, and periodic variations of crime in cities. Though thefts increase super-linearly with the population, we found burglaries showing a linear increase. Our analyses also confirmed crime concentrating spatially regardless of city, with concentration level independent of city size. The results revealed this concentration described approximated with a power-law distribution with exponent α depending on crime type. We confirmed circannual rhythms in the time series and showed this periodicity occurring unevenly across the city. Our results revealed these criminal waves moving across the city: while cities have a stable number of regions with a circannual period, regions display non-stationarity on period. The spatial regularities coupled with the constant changes suggest an understanding of crime as a complex phenomenon—a perspective that demands analyses and evolving urban policies covering the whole city.

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