An Effective Anytime Anywhere Parallel Approach for Centrality Measurements in Social Network Analysis
Santos, E.E.
Long Pan
Arendt, D.
Pittkin, M.
Virginia Polytech Inst., Blacksburg;
This paper appears in: Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Publication Date: 8-11 Oct. 2006
Volume: 6,
On page(s): 4693-4698
Location: Taipei,
ISBN: 1-4244-0099-6
INSPEC Accession Number: 9791011
Digital Object Identifier: 10.1109/ICSMC.2006.385045
Current Version Published: 2007-07-16
Abstract
With the broad application of electronic communication monitoring tools and data-sharing techniques, the size of networks to be studied by social network analysis (SNA) has grown rapidly. However, current SNA techniques are not particularly scalable. For example, even centrality, which is one of the most frequently used SNA parameters, cannot be measured by most current SNA software when the network is large. This paper presents the design of an effective and scalable anytime anywhere parallel methodology for SNA with large-scale networks emphasizing centrality measurement algorithms. The efficiency and effectiveness of the methodology is validated by experiments of centrality analysis for large networks.
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