Friends with Motives: Using Text to Infer Influence on SCOTUS

Yanchuan Sim · Bryan Routledge · Noah A. Smith

15 citations0/0 files storedConference on Empirical Methods in Natural Language Processing (EMNLP)

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Judicial and Constitutional Studies Artificial Intelligence in Law Computational and Text Analysis Methods

Abstract

We present a probabilistic model of the influence of language on the behavior of the U.S. Supreme Court, specifically influence of amicus briefs on Court decisions and opinions.The approach assumes that amici are rational, utility-maximizing agents who try to win votes or affect the language of court opinions.Our model leads to improved predictions of justices' votes and perplexity of opinion language.It is amenable to inspection, allowing us to explore inferences about the persuasiveness of different amici and influenceability of different justices; these are consistent with earlier findings."Language is the central tool of our trade."

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1972Conditional logit analysis of qualitative choice behavior 1995Automobile Prices in Market Equilibrium 2010What Drives Media Slant? Evidence From U.S. Daily Newspapers 2004The Statistical Analysis of Roll Call Data 2002Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999 1985A Spatial Model for Legislative Roll Call Analysis 2006What Drives Media Slant? Evidence from U.S. Daily Newspapers 2017A general approach for predicting the behavior of the Supreme Court of the United States

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2018Predicting Decisions of the Philippine Supreme Court Using Natural Language Processing and Machine Learning

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