Giving every case its (legal) due: The contribution of citation networks and text similarity techniques to legal studies of European Union law

Yannis Panagis*, Urška Šadl, Fabien Tarissan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

5 Citations (Scopus)
2 Downloads (Pure)

Abstract

In this article we propose a novel methodology, which uses text similarity techniques to infer precise citations from the judgments of the Court of Justice of the European Union (CJEU), including their content. We construct a complete network of citations to judgments on the level of singular text units or paragraphs. By contrast to previous literature, which takes into account only explicit citations of entire judgments, we also infer implicit citations, meaning the repetitions of legal arguments stemming from past judgments without explicit reference. On this basis we can differentiate between different categories and modes of citations. The latter is crucial for assessing the actual legal importance of judgments in the citation network. Our study is an important methodological step forward in integrating citation network analysis into legal studies, which significantly enhances our understanding of European Union law and the decision making of the CJEU.

Original languageEnglish
Title of host publicationLegal Knowledge and Information Systems : JURIX 2017: The 30th Annual Conference
EditorsAdam Wyner, Giovanni Casini
Number of pages10
PublisherIOS Press
Publication date2017
Pages59-68
ISBN (Print)978-1-61499-837-2
ISBN (Electronic)978-1-61499-838-9
DOIs
Publication statusPublished - 2017
Event30th International Conference on Legal Knowledge and Information Systems, JURIX 2017 - Luxembourg, Luxembourg
Duration: 13 Dec 201715 Dec 2017

Conference

Conference30th International Conference on Legal Knowledge and Information Systems, JURIX 2017
Country/TerritoryLuxembourg
CityLuxembourg
Period13/12/201715/12/2017
SeriesFrontiers in Artificial Intelligence and Applications
Volume302
ISSN0922-6389

Keywords

  • Citation networks
  • CJEU
  • Network analysis
  • Text similarity

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