Analysis of Legal Argumentation Documents: A Computational Argumentation Approach

This book introduces methods to analyze legal documents using computational argumentation theory, including evaluating argumentation skills from negotiation records and extracting factors and legal topoi from precedents to analyze how they affect judgments. It demonstrates the application of logic-based AI methods to the legal domain and contributes to the education and training of law school students in logical ways of argumentation.

Format: Paperback / softback
Length: 155 pages
Publication date: 14 August 2023
Publisher: Springer Verlag, Singapore

This book presents techniques for analyzing legal documents, such as negotiation records and legal precedents, using computational argumentation theory. First, a method is proposed to automatically assess argumentation skills from argumentation exercise records. Argumentation exercises are frequently conducted in law schools, resulting in numerous records. Each utterance in the record is analyzed to extract a pattern of "speech act + factor," and argumentation skills are evaluated based on the sequences of these patterns using a scoring prediction model constructed through multiple regression analyses between the appearance pattern and the scoring results. The effectiveness of this method is demonstrated by applying it to the "garbage house problem" case. Second, a method is introduced for extracting factors (elements that characterize precedents and cases) and legal topoi from individual precedents and utilizing them as expressions of precedents to analyze how the pattern of factors and legal topoi in a group of precedents affects the judgment (plaintiff wins/defendant wins). This method has been applied to a group of tax cases. Third, the logical structure of 70 labor cases is described in detail by employing factors and a bipolar argumentation framework (BAF) and an extended argumentation framework (EAF) together. BAF describes the logical structure between plaintiff and defendant, while EAF describes the judge's decision. Incorporating legal topoi into the EAF of computational argumentation theory enhances the analysis of precedents by combining factored BAF and EAF. Not only can it be determined which argument the judge adopted, but it is also possible to ascertain the type of value judgment made and verify the logic. The analysis demonstrates the potential of computational argumentation theory in legal reasoning and decision-making.

Dimension: 235 x 155 (mm)
ISBN-13: 9789811929304
Edition number: 1st ed. 2022