Measuring Judicial Sentiment:Methods and Application to U.S. Circuit Courts

26 Pages Posted: 9 Jul 2019 Last revised: 19 Aug 2021

See all articles by Sergio Galletta

Sergio Galletta

University of Bergamo; ETH Zürich

Elliott Ash

ETH Zürich

Daniel L. Chen

Directeur de Recherche, Centre National de la Recherche Scientifique, Toulouse School of Economics, Institute for Advanced Study in Toulouse, University of Toulouse Capitole, Toulouse, France

Date Written: July 19, 2021

Abstract

This paper provides a general method for analyzing the sentiments expressed in the language of judicial rulings. We apply natural language processing tools to the text of U.S. appellate court opinions to extrapolate judges' sentiments (positive/good vs. negative/bad) toward a number of target social groups. We explore descriptively how these sentiments vary over time and across types of judges. In addition, we provide a method for using random assignment of judges in an instrumental variables framework to estimate causal effects of judges' sentiments. In an empirical application, we show that more positive sentiment influences future judges by increasing the likelihood of reversal but also increasing the number of forward citations.

Suggested Citation

Galletta, Sergio and Ash, Elliott and Chen, Daniel L., Measuring Judicial Sentiment:Methods and Application to U.S. Circuit Courts (July 19, 2021). Available at SSRN: https://ssrn.com/abstract=3415393 or http://dx.doi.org/10.2139/ssrn.3415393

Sergio Galletta (Contact Author)

University of Bergamo ( email )

Via Salvecchio, 19
Bergamo, 24129
Italy

ETH Zürich ( email )

Rämistrasse 101
ZUE F7
Zürich, 8092
Switzerland

Elliott Ash

ETH Zürich ( email )

Rämistrasse 101
ZUE F7
Zürich, 8092
Switzerland

Daniel L. Chen

Directeur de Recherche, Centre National de la Recherche Scientifique, Toulouse School of Economics, Institute for Advanced Study in Toulouse, University of Toulouse Capitole, Toulouse, France ( email )

Toulouse School of Economics
1, Esplanade de l'Université
Toulouse, 31080
France

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