Bayesian analysis of urban theft crime in 674 Chinese cities

Current academic research on fitting the volume of urban theft crimes at a macro size is limited, especially from the urban functionality perspective. Given this gap, this study utilizes a Bayesian model to conduct a fitting analysis of theft crime data from 674 cities in China from 2018 to 2020. Th...

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Bibliographic Details
Published in:Scientific reports 2024-11, Vol.14 (1), p.26447-13, Article 26447
Main Authors: Zheng, Haolei, Liu, Daqian, Wang, Yang, Yue, Xiaoli
Format: Article
Language:English
Subjects:
704/172
704/844
Bayesian analysis
Bayesian model
Cities
Cities in China
Crime prevention
Criminology
Economics
Functional size
Geographic information systems
Geography
Humanities and Social Sciences
Land use
multidisciplinary
POI
Science
Science (multidisciplinary)
Socioeconomic factors
Theft crime
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Summary:Current academic research on fitting the volume of urban theft crimes at a macro size is limited, especially from the urban functionality perspective. Given this gap, this study utilizes a Bayesian model to conduct a fitting analysis of theft crime data from 674 cities in China from 2018 to 2020. This research aims to explore novel pathways for theft crime fitting. Results indicate that the size of urban functionality, particularly points of interest (POIs), exhibits excellent performance in fitting theft crimes, with POIs related to public services and commercial activities demonstrating the most significant fitting effects. This research successfully identifies effective indicators for crime fitting, thereby offering a new perspective and supplement to theft crime research. This study holds significant value for gaining a profound understanding of criminal phenomena and explaining the causes and mechanisms underlying the differences in theft crimes among various cities in China.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-77754-3