Author(s)

Li Zipeng ¹

Affiliation(s)

¹ Chengdu University of Technology, Chengdu, Sichuan Province, 610059, China

Corresponding Author

Li Zipeng

ABSTRACT

Presently, artificial intelligence technology is advancing at a rapid pace. Whilst propelling societal development, it has also given rise to a series of AI-related criminal issues. Novel AI criminal methods exhibit extreme concealment and cross-domain characteristics, posing severe challenges to citizens' personal and property safety, social governance order, and judicial credibility. As research into such emerging crimes commenced relatively late, standardised predictions regarding the future evolution and development of AI crime remain lacking. Consequently, this paper will systematise existing AI crime research findings to summarise the research trajectory and future development trends of AI crime over the past decade (2016-2025), providing theoretical reference for subsequent scholarly exploration and research. This study employs quantitative analysis methods, selecting core AI crime-related literature indexed in the CNKI (China National Knowledge Infrastructure) database over the past decade as its data source. Utilising the CiteSpace (version 6.4.R1) visualisation tool, it processes data such as keyword co-occurrence to visualise research trajectories and future trends within the AI crime field. Findings reveal: 1) Analysis of AI crime keyword clustering diagrams indicates existing research has formed five major themes: technology, liability, risk, agency, and governance. Collectively, these constitute a core "one body, two wings, five dimensions" structure, profoundly reflecting academia's efforts to address practical challenges; 2) Analysis of the temporal trend chart for AI crime reveals that research from 2016 to 2025 has progressed from macro-level risk warnings to micro-level precision regulation. Future studies will increasingly emphasise multidisciplinary integration while prioritising responses to practical challenges. Consequently, the research proposes strengthening cross-disciplinary collaboration and establishing ethical governance frameworks to achieve interdisciplinary convergence and develop effective legal systems for risk prevention.

KEYWORDS

Artificial Intelligence Crime, CiteSpace, CNKI (China National Knowledge Infrastructure)

CITE THIS PAPER

Li Zipeng. Analysis of Hotspots and Trends in Artificial Intelligence Crime Research Using CiteSpace: A Case Study of CNKI Data (2016-2025). Science of Law Journal (2025) Vol. 4: 39-46. DOI: http://dx.doi.org/DOI: 10.23977/law.2025.040506.

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