Artificial Intelligence Applied to Crime Prediction: A Bibliometric and Systematic Review of Predictive Models, Spatio-Temporal Data, and Emerging Frontiers

Cayo-Mamani R.I.; Gamboa-Cruzado J.; Nolasco-Valenzuela J.; Chávez-Herrera C.; Salazar-Marzal A.; Gamboa-Cruzado M.; Quesquén Alarcón E.; Núñez-Prado C.J. · Computacion y Sistemas (2026) · DOI: 10.13053/cys-30-1-6344

Resumen

Crime prediction using Artificial Intelligence has increased in technical complexity and public relevance; however, the evidence remains fragmented regarding implementation practices, publication quality, and scientific collaboration. This paper synthesizes and characterizes the literature on Artificial Intelligence applied to Crime Prediction, with emphasis on development languages, quartile levels, co-authorship networks, and thematic categories. A systematic review was conducted following Kitchenham and PRISMA 2020 guidelines, with searches in ProQuest, IEEE Xplore, Scopus, ScienceDirect, and SpringerLink through July 22, 2025. After applying inclusion and exclusion criteria and conducting quality assessment with a threshold of at least 24, 57 studies out of 70 (81.4%) were selected for technical and bibliometric analysis. The results show the dominance of Python as the implementation language (60%), with secondary presence of R (20%) and limited adoption of Java, C++, and Julia at approximately 6.7% each. Production is concentrated in Q1 journals (33/57), followed by Q2 (16/57) and Q3 (8/57), suggesting high visibility, although with heterogeneous impact across sources. Co-authorship analysis reveals core and bridge authors connecting subcommunities, while the thematic map highlights specialized lines such as AI Crime Analytics and AI Policing, as well as marginal topics that are still consolidating. In conclusion, the field is progressing toward more integrated approaches but requires comparable standards, reproducible traceability, and governance frameworks for responsible deployment.

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional de Trujillo; Universidad San Ignacio de Loyola; Universidad Nacional Federico Villarreal