More than Votes? Voting and Language based Partisanship in the US Supreme Court
Submission Type: Regular Short Paper
Submission Track: Computational Social Science and Cultural Analytics
Submission Track 2: Linguistic Theories, Cognitive Modeling, and Psycholinguistics
Keywords: Fairness and Bias; Sociolinguistic; Cultural Analysis; Partisanship Analysis
TL;DR: We propose a framework to investigate language partisanship of justices based on spoken text in court and show a significant correlation between language partisanship and voting ideology.
Abstract: Understanding the prevalence and dynamics of justice partisanship and ideology in the US Supreme Court is critical in studying jurisdiction. Most research quantifies partisanship based on voting behavior, and oral arguments in the courtroom --- the last essential procedure before the final case outcome --- have not been well studied for this purpose. To address this gap, we present a framework for analyzing the language of justices in the courtroom for partisan signals, and study how partisanship in speech aligns with voting patterns.
Our results show that the affiliated party of justices can be predicted reliably from their oral contributions. We further show a strong correlation between language partisanship and voting ideology.
Submission Number: 1189
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