Selecting the cases that defined Europe: Complementary metrics for a network analysis

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

Do case citations reflect the 'real' importance of individual judgments for the legal system concerned? This question has long been puzzling empirical legal scholars. Existing research typically studies case citation networks as a whole applying traditional network metrics stemming from graph theory. Those approaches are able to detect globally important cases, but since they do not take time explicitly into account, they cannot provide a comprehensive account of the dynamics behind the network structure and its evolution. In this paper we provide such a description, using two node importance metrics that take time into account to study important cases in the Court of Justice of the European Union over time. We then compare cases deemed as important by the metrics, with a set of 50 cases selected by the Court as the most important (landmark) cases. Our contribution is twofold. First, with regard to network science, we show that structural and time-related properties are complementary, and necessary to obtain a complete and nuanced picture of the citation network. Second, with regard to the case law of the Court, this study provides empirical evidence clarifying the motivation of the Court when selecting the landmark cases, revealing the importance of symbolic and historical cases in the selection. In addition, the temporal analysis sheds new light on the network properties specific to the landmark cases that distinguishes them from the rest of the cases. We validate our results by providing legal interpretations that sustain the highlights provided by the proposed network analysis.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Number of pages8
PublisherInstitute of Electrical and Electronics Engineers Inc.
Publication date21 Nov 2016
Pages661-668
Article number7752308
ISBN (Electronic)9781509028467
DOIs
Publication statusPublished - 21 Nov 2016
Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
Duration: 18 Aug 201621 Aug 2016

Conference

Conference2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
LandUnited States
BySan Francisco
Periode18/08/201621/08/2016
SponsorACM SIGMOD, Association for Computing Machinery (ACM), et al., IEEE, IEEE Computer Society, IEEE TCDE

    Research areas

  • Authority scores, Average longevity, Citation networks, Directed acyclic graphs, European Court of Justice, Relative in-degree

ID: 203178041