Finding Criminal Attractors Based on Offenders' Directionality of Crimes (original) (raw)
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Power of Criminal Attractors: Modeling the Pull of Activity Nodes
2011
The spatial distribution of crime has been a long-standing interest in the field of criminology. Research in this area has shown that activity nodes and travel paths are key components that help to define patterns of offending. Little research, however, has considered the influence of activity nodes on the spatial distribution of crimes in crime neutral areas -those where crimes are more haphazardly dispersed. Further, a review of the literature has revealed a lack of research in determining the relative strength of attraction that different types of activity nodes possess based on characteristics of criminal events in their immediate surrounds. In this paper we use offenders' home locations and the locations of their crimes to define directional and distance parameters. Using these parameters we apply mathematical structures to define rules by which different models may behave to investigate the influence of activity nodes on the spatial distribution of crimes in crime neutral areas. The findings suggest an increasing likelihood of crime as a function of geometric angle and distance from an offender's home location to the site of the criminal event. Implications of the results are discussed.
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This article discusses how the use of cellular networks by a criminal offender produces spatio-temporal data that reveals his/her activities and activity space. The methods aim to establish possible paths that the criminal will use to move around in his/her activity space; the edges of the activity space; districts in which the criminal is moving such as residential, commercial and industrial areas and attractions such as night clubs and warehouses; and nodes determined by the frequency of cell usage. Using cellular location usage data, it is possible to determine the criminal’s mental map of the area in which he/she operates based on routine activity theory approach as well as establishing the criminal’s comfort zone. Such information can be valuable for intelligence and investigative purposes.
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Journal of the Royal Statistical Society: Series C (Applied Statistics), 2013
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2012
— In the current study we develop a Criminal Movement Model (CriMM) to investigate the relationship between simulated travel routes of offenders along the physical road network and the actual locations of their crimes in the same geographic space. With knowledge of offenders ’ home locations and the locations of major attractors, we are able to model the routes that offenders are likely to take when travelling from their home to an attractor by employing variations of Dijkstra’s shortest path algorithm. With these routes plotted, we then compare them to the locations of crimes committed by the same offenders. This model was applied to five attractor locations within the Greater Vancouver Regional District (GVRD) in the province of British Columbia, Canada. Information about offenders in these cities was obtained from five years worth of real police data. After performing a small-scale analysis for each offender to investigate how far off their shortest path they go to commit crimes,...
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