Abstract
The increasing adoption of artificial intelligence (AI) in legal document analysis presents opportunities for improved contract interpretation and study. This research explores the use of BERTopic Dynamic Topic Modeling to analyze commercial contract clauses, identifying evolving trends in legal language and contractual structures. Using the Contract Understanding Atticus Dataset (CUAD), this research examines common contract clauses such as governing law, audit rights, and liability caps to uncover patterns across different industries, time periods, clause types, and jurisdictions. Using transformer-based embeddings, clustering techniques, and topic modeling, this research provides information on legal language shifts, the role of AI in contract review, and potential implications for legal practitioners and businesses. The findings demonstrate the ability of AI to improve contract analysis while highlighting key challenges in interpretability and legal transparency. This research contributes to the growing field of AI-driven legal analytics and suggests avenues for future research on automated contract evaluation.
Advisor
Musgrave, John
Department
Computer Science
Recommended Citation
Johnson, Patrick, "Commercial Contract Clause Analysis Using BERTopic Dynamic Topic Modeling" (2025). Senior Independent Study Theses. Paper 11562.
https://openworks.wooster.edu/independentstudy/11562
Disciplines
Artificial Intelligence and Robotics | Data Science
Publication Date
2025
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2025 Patrick Johnson