An apex court’s body of cases has an internal texture, continually augmented by recent citations to earlier, topically related cases. How can we best describe that texture? The citation network shows a path. Specifically, what past Supreme Court cases do more recent Supreme Court cases tend to cite together, as if a topical pair? Using a web of those oft-cited pairs, what noun phrases appear in a given cluster of cases more often, relative to the rate at which those phrases appear in writings more generally? To answer these questions is to map, in detail, a body of decisional law. Using common network-analysis and corpus-linguistics tools, one can derive from a group of cases the key empirical facets of the legal doctrine embodied in that cluster of cases — a semantic self-portrait that the cases paint with their own words and citations. This paper provides a pair of case studies for revealing the latent semantic building blocks of legal doctrine. First, using a new citation dataset, I analyze the co-citation network of a sharply defined group of Supreme Court cases (in this instance, cases on the Warsaw Convention, a treaty that limits liability for loss or injury in international air travel, and other cases related thereto). Second, building on a citation dataset from prior work, I analyze the co-citation network of all the Supreme Court’s intellectual property cases from 1947 to 2018, inclusive. With these empirical studies, I show that co-citation analysis complements both traditional legal analysis — by establishing data about legal doctrine, from the bottom up, using large case networks — and the attitudinal-model studies from political science — by focusing on the substance of legal doctrine, rather than on judges’ votes in split cases placed on a right-left continuum.
Joseph S. Miller,
Law's Semantic Self-Portrait: Discerning Doctrine with Co-Citation Networks and Keywords
, 81 U. Pitt. L. Rev. 1
Available at: https://digitalcommons.law.uga.edu/fac_artchop/1318