Conference proceeding
An effective anytime anywhere parallel approach for centrality measurements in social network analysis
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, v 6, pp 4693-4698
01 Jan 2006
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 validaled by experiments of centrality analysis for large networks.
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Details
- Title
- An effective anytime anywhere parallel approach for centrality measurements in social network analysis
- Creators
- Eunice E. Santos - Virginia TechLong Pan - Virginia TechDustin Arendt - Virginia TechMorgan Pittkin - Virginia Tech
- Publication Details
- 2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, v 6, pp 4693-4698
- Series
- IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- FA9550-06-1-0619 / AFOSR; United States Department of Defense; Air Force Office of Scientific Research (AFOSR)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- School of Engineering
- Web of Science ID
- WOS:000248078505043
- Scopus ID
- 2-s2.0-34548128479
- Other Identifier
- 991022207050604721