Aoristic crime analysis

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Abstract
Crime pattern analysis has tended to focus on 'hotspot' analysis techniques; the identification of areas with higher densities of criminal activity. This paper documents a different approach to determination of hotspots and aims to present a conceptual framework for the temporal analysis of aoristic crime data. This analysis monitors the change in crime patterns over time and can be applied to arbitrary areas, especially those smaller than police beat boundaries, which have been traditionally the smallest resolution areal unit studied within most British police forces. It also clarifies examination of lower crime areas, which can be overlooked in other forms of analysis. Crime data often lacks temporal definition and three different methods of temporal search technique are compared. Results from a new aoristic approach highlight a weekly Monday peak in motor vehicle crime on one division of Nottinghamshire Constabulary. In another example a historically weighted temporal model helps identify rising or falling crime rates.

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