AI-driven crime prediction: a bibliometric analysis of contributions from South Asian authors

Purpose This study aims to fill a prominent gap in identifying the contributions of South Asian researchers to the field of crime prediction, leveraging advanced Artificial Intelligence (AI) techniques. By conducting a bibliometric analysis, this research investigates regional efforts in applying artificial intelligence to analyze and predict crime, addressing the specific roles and impact of South Asian scholars in this global domain. Design/methodology/approach For analysis, the authors used a structured query on the Scopus database. A total of 1,325 documents were retrieved; however, only 628 relevant studies were selected after a rigorous filtering process. The selected documents were analyzed for publication trends, country-specific contributions, notable authors and institutions, citation trajectories and popular publishing venues. Findings This study observed a significant increase in publication output, with an annual growth rate of 15.5%, which underscores the region’s growing interest and recognition of AI’s potential in crime prediction. India leads in this field, contributing 537 documents, while the Maldives, Nepal and Bhutan reported no publications. Moreover, a total of 387 different publication venues were observed, with IEEE Access being the most frequent, by publishing 10 documents. Research limitations/implications The study relies solely on Scopus-indexed documents, potentially excluding valuable work from non-indexed or local journals. The bibliometric approach emphasizes quantitative trends and does not account for the qualitative depth, societal relevance or implementation outcomes of the research. Language and regional biases may have influenced inclusion, as only English-language publications were considered. Practical implications Unveiling the bibliometric trends and insights of advanced AI-based techniques for crime prediction and summarizing them in one place can help policymakers, law enforcement agencies and researchers make informed decisions and foster collaborations (Campedelli, 2021). It can help a new researcher in the field to find prominent scientists and institutions to collaborate with. Moreover, by shedding light on the underexplored contributions of South Asian researchers in the field of AI-based crime prediction, this research not only fills a critical knowledge void but also paves the way for more inclusive and representative global discourse in technological advancements. Furthermore, the study provides policymakers and law enforcement agencies with valuable insights into how AI is being leveraged in diverse socio-political contexts, enabling more tailored and effective crime prevention strategies. Ultimately, the bibliometric evidence gathered serves as a strategic resource for shaping future research directions, enhancing regional visibility and guiding investment in AI-driven public safety initiatives. Originality/value To the best of the authors’ knowledge, this study is the first to offer a detailed bibliometric analysis of AI-driven crime prediction research specific to South Asian authors. By identifying contributions and investigating collaborative and publishing patterns, the research provides a foundation for advancing regional efforts. This study helps to identify the leading institutions and authors in South Asia working in the domain of crime prediction, enabling future academic and interdisciplinary collaborations.