Abstract

http://ssrn.com/abstract=1442880
 
 

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On the Stability of Community Detection Algorithms on Longitudinal Citation Data


Michael James Bommarito II


Bommarito Consulting, LLC

Daniel Martin Katz


Michigan State University - College of Law

Jon Zelner


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

August 2, 2009

Procedia Social and Behavioral Sciences, 2010
Proceedings of the 6th Conference on Applications of Social Network Analysis (ASNA 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.

Number of Pages in PDF File: 12

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

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Date posted: August 4, 2009 ; Last revised: May 26, 2010

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: http://ssrn.com/abstract=1442880

Contact Information

Michael James Bommarito II
Bommarito Consulting, LLC ( email )
Troy, MI 48098
United States
16464503387 (Phone)
HOME PAGE: http://bommaritollc.com/
Daniel Martin Katz (Contact Author)
Michigan State University - College of Law ( email )
230F Law College Building
East Lansing, MI 48824-1300
United States
HOME PAGE: http://computationallegalstudies.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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