Big data and AI-driven evidence analysis: a global perspective on citation trends, accessibility, and future research in legal applications

Abstract

This study explores the integration of Big Data and Artificial Intelligence (AI) in the context of legal evidence analysis, focusing on citation and download trends of academic papers across various countries. Our analysis highlights key geographical patterns in citation distribution, revealing the global recognition of AI-driven research in legal contexts. The increasing number of annual downloads indicates growing interest and accessibility in this field. By applying statistical methods, we examine regional variations in legal systems using regression analysis and hypothesis testing, AI adoption rates, and cultural factors influencing AI technologies. The study also addresses uncertainties and potential biases, using uncertainty analysis to assess the robustness of our findings. In addition, we identify research gaps and propose future directions for utilizing Big Data and AI in image analysis for legal evidence, aiming to foster interdisciplinary collaboration and further advancements in this critical area.

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