On the Stability of Community Detection Algorithms on Longitudinal Citation Data

Procedia Social and Behavioral Sciences, 2010

Proceedings of the 6th Conference on Applications of Social Network Analysis (ASNA 2009)

12 Pages Posted: 4 Aug 2009 Last revised: 26 May 2010

Michael James Bommarito II

LexPredict, LLC; Bommarito Consulting, LLC; Chicago-Kent College of Law - Illinois Institute of Technology; Michigan State College of Law

Daniel Martin Katz

Illinois Tech - Chicago Kent College of Law

Jon Zelner

University of Michigan at Ann Arbor - Center for Study of Complex Systems

Date Written: August 2, 2009

Abstract

There are fundamental differences between citation networks and other classes of graphs. In particular, given that citation networks are directed and acyclic, methods developed primarily for use with undirected social network data may face obstacles. This is particularly true for the dynamic development of community structure in citation networks. Namely, it is neither clear when it is appropriate to employ existing community detection approaches nor is it clear how to choose among existing approaches. Using simulated data, we attempt to clarify the conditions under which one should use existing methods and which of these algorithms is appropriate in a given context. We hope this paper will serve as both a useful guidepost and an encouragement to those interested in the development of more targeted approaches for use with longitudinal citation data.

Keywords: community detection, evolutionary graph theory, computational legal studies, citation network, direct acyclic graphs, graph theory, network analysis and law, judicial citation network, network dynamics

JEL Classification: C60, C61, C63, C88, C8

Suggested Citation

Bommarito, Michael James and Katz, Daniel Martin and Zelner, Jon, On the Stability of Community Detection Algorithms on Longitudinal Citation Data (August 2, 2009). Procedia Social and Behavioral Sciences, 2010; Proceedings of the 6th Conference on Applications of Social Network Analysis (ASNA 2009). Available at SSRN: https://ssrn.com/abstract=1442880

Michael James Bommarito II

LexPredict, LLC ( email )

MI
United States

HOME PAGE: http://lexpredict.com

Bommarito Consulting, LLC ( email )

MI 48098
United States

HOME PAGE: http://bommaritollc.com

Chicago-Kent College of Law - Illinois Institute of Technology ( email )

565 W. Adams St.
Chicago, IL 60661-3691
United States

Michigan State College of Law ( email )

318 Law College Building
East Lansing, MI 48824-1300
United States

Daniel Martin Katz (Contact Author)

Illinois Tech - Chicago Kent College of Law ( email )

565 W. Adams St.
Chicago, IL 60661-3691
United States

HOME PAGE: http://www.danielmartinkatz.com/

Jon Zelner

University of Michigan at Ann Arbor - Center for Study of Complex Systems ( email )

321A West Hall
Ann Arbor, MI 48109
United States

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