Article,

The network structure of supreme court jurisprudence

.
University of Houston Law Center, (Jun 10, 2005)

Abstract

In common law jurisdictions such as the United States, courts frequently resolve disputes by citation and analysis of reports of prior legal cases. The law may thus be thought of as a giant network containing textual information embedded in cases (nodes) and relationship information called citations (arcs) going from node to node. In recent years, the science of studying networks has developed and, while there had been some rudimentary attempts to look at subsets of the vast legal network, until recently there had been little done to take advantage of modern technology and modern network theory in that effort. This is a somewhat technical article written for a Mathematica conference that borrows techniques developed largely in sociology and physics to learn about Supreme Court jurisprudence simply by a study of its network structure. It is very much complementary to the work of Professor Thomas A. Smith of the University of San Diego Law School on "The Web of Law." Although the first half of the paper focuses on tool building and computer science issues in a way that may put off more law-oriented readers, the second half of the article relates quite directly to the law. It shows that federal jurisdiction and commerce clause cases are, quite literally, central to Supreme Court jurisprudence. It argues that the degree distribution of the Supreme Court network does not quite fit that of a scale free network but rather fits more closely that of a Weibull distribution, which is generated by the lifetime of objects. It suggests that rights of free speech and association may lie at the "core" of Supreme Court jurisprudence and thus pose issues of particular complexity. It is my hope that this article, along with other recent work, will catalyze a set of studies in this field that will expand to cover other judicial systems and yet more sophisticated analysis of the rich network information they contain.

Tags

Users

  • @olitazl
  • @muehlburger

Comments and Reviews