Publication Type

Journal Article

Version

publishedVersion

Publication Date

4-2024

Abstract

Complexity science provides a powerful framework for understanding physical, biological and social systems, and network analysis is one of its principal tools. Since many complex systems exhibit multilateral interactions that change over time, in recent years, network scientists have become increasingly interested in modelling and measuring dynamic networks featuring higher-order relations. At the same time, while network analysis has been more widely adopted to investigate the structure and evolution of law as a complex system, the utility of dynamic higher-order networks in the legal domain has remained largely unexplored. Setting out to change this, we introduce temporal hypergraphs as a powerful tool for studying legal network data. Temporal hypergraphs generalize static graphs by (i) allowing any number of nodes to participate in an edge and (ii) permitting nodes or edges to be added, modified or deleted. We describe models and methods to explore legal hypergraphs that evolve over time and elucidate their benefits through case studies on legal citation and collaboration networks that change over a period of more than 70 years. Our work demonstrates the potential of dynamic higher-order networks for studying complex legal systems, and it facilitates further advances in legal network analysis.This article is part of the theme issue ‘A complexity science approach to law and governance’.

Keywords

complex systems, higher-order networks, hypergraphs, legal complexity, legal networks, temporal networks

Discipline

Science and Technology Law

Research Areas

Innovation, Technology and the Law

Publication

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Volume

382

Issue

2270

First Page

1

Last Page

19

ISSN

1364-503X

Identifier

10.1098/rsta.2023.0141

Publisher

The Royal Society

Additional URL

https://doi.org/10.1098/rsta.2023.0141

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