Unveiling wildlife crime characteristics in China based on judicial big data

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.