Network Analysis and the Law: Measuring the Legal Importance of Precedents at the U.S. Supreme Court

TLDR

The study proposes a method that uses citation patterns to assign importance scores to Supreme Court precedents, identifying the most legally relevant cases at any time. The authors build a complete network of 26,681 Supreme Court majority opinions and their citations from 1791 to 2005, then apply a citation‑pattern analysis to generate importance scores. The resulting importance scores outperform existing network metrics, correlate strongly with future citations by lower courts, and demonstrate that network analysis can effectively measure a case’s legal centrality and other legal concepts.

Abstract

We construct the complete network of 26,681 majority opinions written by the U.S. Supreme Court and the cases that cite them from 1791 to 2005. We describe a method for using the patterns in citations within and across cases to create importance scores that identify the most legally relevant precedents in the network of Supreme Court law at any given point in time. Our measures are superior to existing network-based alternatives and, for example, offer information regarding case importance not evident in simple citation counts. We also demonstrate the validity of our measures by showing that they are strongly correlated with the future citation behavior of state courts, the U.S. Courts of Appeals, and the U.S. Supreme Court. In so doing, we show that network analysis is a viable way of measuring how central a case is to law at the Court and suggest that it can be used to measure other legal concepts.