Unveiling wildlife crime characteristics in China based on judicial big data
Abstract Wildlife crime is a global issue of significant concern. To investigate the current situation of wildlife crime in China, a study was conducted using criminal judgment documents from China Judgments Online, covering the period from 2013 to 2018. This paper introduces a characteristic mining...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | Discover Sustainability |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43621-025-01824-3 |
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| Summary: | Abstract Wildlife crime is a global issue of significant concern. To investigate the current situation of wildlife crime in China, a study was conducted using criminal judgment documents from China Judgments Online, covering the period from 2013 to 2018. This paper introduces a characteristic mining method for wildlife crime based on judicial big data. By extracting multi-dimensional characteristics of cases—such as subjects, time, space, and category—the study constructs a big data portrait of wildlife crime. The results reveal key patterns, including the presence of organized criminal groups, uneven spatio-temporal distribution, and a mixed approach to punishment, combining leniency with strictness. Furthermore, corresponding countermeasures for crime management are proposed. The insights derived from judicial big data mining provide a deeper understanding of the laws governing wildlife crime and offer practical guidance for targeted prevention, enforcement, and decision-making in wildlife resource protection. |
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| ISSN: | 2662-9984 |