Physica A, Vol. 389, pp. 4201-4208, 2010
8 Pages Posted: 11 Sep 2009 Last revised: 9 Nov 2010
Date Written: September 11, 2009
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.
Keywords: citation networks, acyclic digraphs, dynamic network analysis, judicial citations, patent citations, distance measures, community detection, clustering
JEL Classification: C61, C63, C60, C88
Suggested Citation: Suggested Citation
Bommarito, Michael James and Katz, Daniel Martin and Zelner, Jon and Fowler, James H., Distance Measures for Dynamic Citation Networks (September 11, 2009). Physica A, Vol. 389, pp. 4201-4208, 2010. Available at SSRN: https://ssrn.com/abstract=1472037