Studying Judicial Behavior with Text Analysis

Forthcoming Oxford Handbook of Comparative Judicial Behavior

Virginia Public Law and Legal Theory Research Paper No. 2023-71

16 Pages Posted: 16 Oct 2023

See all articles by Bao Kham Chau

Bao Kham Chau

Cornell University - Cornell Tech NYC; Rebooting Social Media Initiative

Michael A. Livermore

University of Virginia School of Law

Date Written: October 16, 2023

Abstract

This chapter provides an overview of computational text analysis techniques used to study judicial behavior and decision-making. As legal texts become increasingly digitized, scholars can draw on tools from machine learning and natural language processing to convert unstructured texts into quantitative data amenable to empirical analysis. The chapter surveys common methods for representing legal documents and discusses their strengths and weaknesses. Each approach makes tradeoffs between richness of representation and dimensionality reduction. Extracting meaningful data from legal texts requires thoughtful choices about representation and preprocessing. The chapter discusses interpretability, bias, and domain-specific challenges as important considerations when applying text analysis to study courts. Overall, computational text analysis supplements traditional methods and opens new avenues for empirical legal scholarship.

Keywords: natural language processing, computational text analysis, machine learning, empirical legal studies, text as data

Suggested Citation

Chau, Bao Kham and Livermore, Michael A., Studying Judicial Behavior with Text Analysis (October 16, 2023). Forthcoming Oxford Handbook of Comparative Judicial Behavior, Virginia Public Law and Legal Theory Research Paper No. 2023-71, Available at SSRN: https://ssrn.com/abstract=4603574 or http://dx.doi.org/10.2139/ssrn.4603574

Bao Kham Chau

Cornell University - Cornell Tech NYC ( email )

111 8th Avenue #302
New York, NY 10011
United States

Rebooting Social Media Initiative ( email )

William James Hall, Sixth Floor
33 Kirkland Street
Cambridge, MA 02138
United States

Michael A. Livermore (Contact Author)

University of Virginia School of Law ( email )

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