Amanda Herbert (Quinnipiac University – Lender School of Business), Dhruv Khanna (Quinnipiac University), & Emmanuel Chigowe (Quinnipiac University – Lender School of Business) have posted Text Analysis in the Legal Domain: Uncovering Patterns in Court Rulings and Legal Opinions using AI on SSRN. Here is the abstract:
The integration of Artificial Intelligence (AI) into the legal field is reshaping how legal professionals interpret, process, and utilize judicial texts. This study investigates the application of Natural Language Processing (NLP) and machine learning techniques to analyze court rulings and legal opinions, aiming to uncover hidden linguistic patterns, sentiment trends, and inconsistencies in judicial reasoning. By leveraging AI-driven text analysis, the research explores how automated tools can enhance legal research, support predictive modeling of case outcomes, and contribute to a more transparent and efficient legal system. The study focuses on large-scale legal corpora from common law jurisdictions and employs a combination of pattern recognition, sentiment detection, and classification models. The findings highlight the potential of AI to not only assist legal practitioners but also transform the broader landscape of legal scholarship and policymaking. This research offers practical insights into how technology can augment traditional methods of legal analysis, raising important considerations around ethics, bias, and the future role of AI in the justice system.