Posts Tagged ‘Statistical analysis of legal information’

Boulet, Mazzega, and Bourcier on A Network Approach to the French System of Legal Codes Part 1

December 30, 2011

Dr. Romain Boulet of UMR ESPACE-DEV, IRD; Dr. Pierre Mazzega of UnB/IRD and UPS (OMP), CNRS, IRD; and Dr. Danièle Bourcier of CERSA CNRS, have published A network approach to the French system of legal codes—part I: analysis of a dense network, Artificial Intelligence and Law, 19, 333-355 (2011). Here is the abstract:

We explore one aspect of the structure of a codified legal system at the national level using a new type of representation to understand the strong or weak dependencies between the various fields of law. In Part I of this study, we analyze the graph associated with the network in which each French legal code is a vertex and an edge is produced between two vertices when a code cites another code at least one time. We show that this network distinguishes from many other real networks from a high density, giving it a particular structure that we call concentrated world and that differentiates a national legal system (as considered with a resolution at the code level) from small-world graphs identified in many social networks. Our analysis then shows that a few communities (groups of highly wired vertices) of codes covering large domains of regulation are structuring the whole system. Indeed we mainly find a central group of influent codes, a group of codes related to social issues and a group of codes dealing with territories and natural resources. The study of this codified legal system is also of interest in the field of the analysis of real networks. In particular we examine the impact of the high density on the structural characteristics of the graph and on the ways communities are searched for. Finally we provide an original visualization of this graph on an hemicyle-like plot, this representation being based on a statistical reduction of dissimilarity measures between vertices. In Part II (a following paper) we show how the consideration of the weights attributed to each edge in the network in proportion to the number of citations between two vertices (codes) allows deepening the analysis of the French legal system.

JURIX 2011: Accepted Papers

October 19, 2011

Accepted papers have been announced for JURIX 2011: The International Conference on Legal Knowledge and Information Systems, to be held 14-16 December 2011, at the University of Vienna Centre for Legal Informatics, in Vienna, Austria.

Bommarito et al. on Distance Measures for Dynamic Citation Networks

September 29, 2009

Michael James Bommarito II, Daniel Martin Katz, & Jon Zelner, all of the University of Michigan at Ann Arbor, Center for Study of Complex Systems, & Professor James H. Fowler of the University of California, San Diego, Department of Political Science, have published Distance Measures for Dynamic Citation Networks on SSRN. Here is the abstract:

“Acyclic digraphs arise in many natural and artificial processes. Among
the broader set, dynamic citation networks represent a substantively
important form of acyclic digraphs. For example, the study of such
networks includes the spread of ideas through academic citations, the
spread of innovation through patent citations, and the development of
precedent in common law systems. The specific dynamics that produce
such acyclic digraphs not only differentiate them from other classes of
graphs, but also provide guidance for meaningful distance measures for these networks. We apply our sink based distance measure and the single-linkage hierarchical clustering algorithm to the first quarter century of decisions of the United States Supreme Court. Despite applying the simplest distance measure and a straight forward clustering algorithm, qualitative analysis reveals that accurate clusterings are produced by this scheme.”


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