Case Vectors: Spatial Representations of the Law Using Document Embeddings

Chen, Daniel L. and Ash, Elliott (2019) Case Vectors: Spatial Representations of the Law Using Document Embeddings. Computational Analysis of Law. (In Press)

Full text not available from this repository.
Official URL: http://tse-fr.eu/pub/33351

Abstract

Recent work in natural language processing represents language objects (words and documents) as dense vectors that encode the relations between those objects. This paper explores the application of these methods to legal language, with the goal of understanding judicial reasoning and the relations between judges. In an application to federal appellate courts, we show that these vectors encode information that distinguishes courts, time, and legal topics. The vectors do not reveal spatial distinctions in terms of political party or law school attended, but they do highlight generational differences across judges. We conclude the paper by outlining a range of promising future applications of these methods.

Item Type: Article
Language: English
Date: 2019
Refereed: Yes
Additional Information: ATTENTE DE PUBLICATION NN 16/07/2019
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 06 Feb 2019 15:26
Last Modified: 08 Oct 2019 23:06
["eprint_fieldname_oai_identifier" not defined]: oai:tse-fr.eu:33351
URI: http://publications.ut-capitole.fr/id/eprint/31266

Actions (login required)

View Item View Item