Jiang, X. orcid.org/0000-0003-4255-5445, Breskaya, M. orcid.org/0009-0006-1245-0043 and van Dijck, G. orcid.org/0000-0003-4102-4415 (2026) Tracking the evolution of case law with main path analysis. Artificial Intelligence and Law. ISSN: 0924-8463
Abstract
Understanding case law evolution contributes to the comprehension of legal principles, the identification of trends in judicial reasoning, and testing consistency between judgments. Automation of the analysis has the potential to make it easier to keep up with relevant case law. While legal network analysis typically focuses on identifying precedents, it has largely overlooked tracking historical developments in judicial reasoning. This study applies Main Path Analysis (MPA) to legal citation networks to uncover how key decisions have shaped the law over time. This study illustrates MPA with consumer protection law cases decided by the Court of Justice of the European Union (CJEU). MPA was applied to a citation network of 446 consumer rights cases from 1980 to Oct 2023. The method involves two steps: (1) weighting citations to measure knowledge flow and (2) extracting significant paths that trace the evolution of judicial reasoning. The Top-3 key-route main paths from five time slices were merged into an overlay network and analysed for alignment with judicial interpretations and evolving consumer protection themes. The topics on the paths are compared to those prevalent in the literature on consumer protection. The analysis uncovered key paths in consumer protection jurisprudence shaped by pivotal cases. Organised around five themes—unfair terms, equivalent effect, comparative advertising, free movement of goods, and product liability— paths align closely with the CJEU’s interpretative practices. While MPA highlights significant pathways, it has caveats and challenges, particularly in achieving comprehensive and representative results and in large networks. Future improvements could include integrating semantic adjustments and key case identification to enhance both aspects, as well as developing complementary methods to identify derivative or branching paths in domain development.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Main path analysis; Network analysis; Case law; Evolution; Consumer protection |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Information, Journalism and Communication |
| Date Deposited: | 15 Jul 2026 11:57 |
| Last Modified: | 15 Jul 2026 11:57 |
| Status: | Published online |
| Publisher: | Springer Science and Business Media LLC |
| Refereed: | Yes |
| Identification Number: | 10.1007/s10506-026-09523-8 |
| Related URLs: | |
| Sustainable Development Goals: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:243421 |


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