Shiode, N. and Shiode, Shino and Nishi, H. and Hino, K. (2023) Seasonal characteristics of crime: an empirical investigation of the temporal fluctuation of the different types of crime in London. Computational Urban Science 3 (19), ISSN 2730-6852.
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Abstract
Most types of crimes show seasonal fluctuations but the difference and similarity between the periodicity of crimes is understudied. Interpreting the seasonality of different crime types and formulating clusters of crimes that share similar seasonal characteristics would help identify the common underlying factors and revise the patterns of patrolling and monitoring to enable sustained management of the control strategies. This study proposes a new methodological framework for measuring similarities and differences in the timing of peaks and troughs, as well as the waveforms of different crimes. The method combines a Poisson state-space model with cluster analysis and multi-dimensional scaling. A case study using 12 types of crimes in London (2013–2020) demonstrated the amplitude of the seasonal fluctuation identified by this method explained 95.2% of the similarity in their waveforms, while the timing of the peaks covered 87.5% of the variance in their seasonal fluctuation. The high predictability of the seasonal patterns of crimes as well as the stable categorisation of crimes with similar seasonal characteristics enable sustainable and measured planning of police resource allocation and, thereby, a more efficient management of the urban environment.
Metadata
| Item Type: | Article |
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| Keyword(s) / Subject(s): | Cluster analysis, Crime seasonality, Multi-dimensional scaling, Trend analysis, Urban sustainability |
| School: | Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences |
| Depositing User: | Shino Shiode |
| Date Deposited: | 05 May 2023 13:03 |
| Last Modified: | 02 Aug 2023 18:21 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/51166 |
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