Work

Bayesian analysis of urban theft crime in 674 Chinese cities

Year: 2024

Type: article

Abstract: 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.

Source: Scientific Reports

Authors: Haolei Zheng, Daqian Liu, Yang Wang, Xiaoli Yue

Institutions: Yunnan Normal University, Chinese Academy of Sciences, Northeast Institute of Geography and Agroecology

Language: English

Topic: Crime Patterns and Interventions

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Peace, justice, and strong institutions

Open Access status: gold

Estimated APC paid: $2,590

Funder: National Natural Science Foundation of China