Text-mining for Lawyers: How Machine Learning Techniques Can Advance our Understanding of Legal Discourse

25 Pages Posted: 4 Dec 2020

See all articles by Arthur Dyevre

Arthur Dyevre

Leuven Centre for Empirical Jurisprudence

Date Written: November 20, 2020

Abstract

Many questions facing legal scholars and practitioners can only be answered by analysing and interrogating large collections of legal documents: statutes, treaties, judicial decisions and law review articles. I survey a range of novel techniques in machine learning and natural language processing – including topic modelling, word embeddings and transfer learning – that can be applied to the large-scale investigation of legal texts.

Keywords: law; natural language processing; text-mining; machine learning; supervised methods; unsupervised methods

Suggested Citation

Dyevre, Arthur, Text-mining for Lawyers: How Machine Learning Techniques Can Advance our Understanding of Legal Discourse (November 20, 2020). Available at SSRN: https://ssrn.com/abstract=3734430 or http://dx.doi.org/10.2139/ssrn.3734430

Arthur Dyevre (Contact Author)

Leuven Centre for Empirical Jurisprudence ( email )

Tiensestraat 41
Leuven, B-3000
Belgium
+32492971322 (Phone)

HOME PAGE: http://www.arthurdyevre.org

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