Large-scale structure of time evolving citation networks
E. A. Leicht (),
G. Clarkson,
K. Shedden and
M. E.J. Newman
The European Physical Journal B: Condensed Matter and Complex Systems, 2007, vol. 59, issue 1, 75-83
Abstract:
In this paper we examine a number of methods for probing and understanding the large-scale structure of networks that evolve over time. We focus in particular on citation networks, networks of references between documents such as papers, patents, or court cases. We describe three different methods of analysis, one based on an expectation-maximization algorithm, one based on modularity optimization, and one based on eigenvector centrality. Using the network of citations between opinions of the United States Supreme Court as an example, we demonstrate how each of these methods can reveal significant structural divisions in the network and how, ultimately, the combination of all three can help us develop a coherent overall picture of the network's shape. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2007
Keywords: 89.75.Hc Networks and genealogical trees; 89.75.Fb Structures and organization in complex systems; 89.70.+c Information theory and communication theory (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (15)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:eurphb:v:59:y:2007:i:1:p:75-83
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DOI: 10.1140/epjb/e2007-00271-7
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