Tharaka Alahakoon
Rahul Tripathi
Adriana Iamnitchi
ABSTRACT
This paper proposes an alternative way to identify nodes with high betweenness centrality. It introduces a new metric, κ-path centrality, and a randomized algorithm for estimating it, and shows empirically that nodes with high κ-path centrality have high node betweenness centrality. Experimental evaluations on diverse real and synthetic social networks show improved accuracy in detecting high betweenness centrality nodes and significantly reduced execution time when compared to known randomized algorithms.
- T. Alahakoon, R. Tripathi, N. Kourtellis, R. Simha, and A. Iamnitchi. K-path centrality: A new centrality measure in social networks. http://www.csee.usf.edu/~tripathi/kpath-centrality.pdf.Google Scholar
- J. Anthonisse. The rush in a directed graph. Technical Report BN9/71, Stichting Mathematisch Centrum, Amsterdam, Netherlands, 1971.Google Scholar
- D. Bader, S. Kintali, K. Madduri, and M. Mihail. Approximating betweenness centrality. In WAW, pages 124--137, 2007. Google ScholarDigital Library
- V. Batagelj and A. Mrvar. Pajek datasets. http://vlado.fmf.unilj.si/pub/networks/data/, 2006.Google Scholar
- U. Brandes. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2):163--177, 2001.Google ScholarCross Ref
- U. Brandes and C. Pich. Centrality estimation in large networks. I. J. of Bifurcation and Chaos, 17(7):2303--2318, 2007.Google ScholarCross Ref
- D. Eppstein and J. Wang. Fast approximation of centrality. J. of Graph Algorithms & Applications, 8(1):39--45, 2004.Google Scholar
- C. Freeman, S. Borgatti, and D. White. Centrality in valued graphs: A measure of betweenness based on network flow. Social Networks, 13(2):141--154, 1991.Google ScholarCross Ref
- L. Freeman. A set of measures of centrality based on betweenness. Sociometry, 40(1):35--41, 1977.Google ScholarCross Ref
- N. Friedkin. Horizons of observability and limits of informal control in organizations. Social Forces, 62(1):57--77, 1983.Google ScholarCross Ref
- A. Iamnitchi, M. Ripeanu, and I. Foster. Small-world file-sharing communities. In INFOCOM, pages 952--963, 2004. Google ScholarDigital Library
- R. Jacob, D. Koschützki, K. Lehmann, L. Peeters, and D. Podehl. Algorithms for centrality indices. In Network Analysis, pages 62--82. Springer-Verlag LNCS #3418, 2005.Google Scholar
- H. Jeong, S. Mason, A. Barabási, and Z. Oltvai. Lethality and centrality in protein networks. Nature, 411:41, 2001.Google ScholarCross Ref
- G. Kahng, E. Oh, B. Kahng, and D. Kim. Betweenness centrality correlation in social networks. Phys. Rev. E, 67:01710--1, 2003.Google Scholar
- J. Leskovec. Stanford large network dataset collection. http://snap.stanford.edu/data/, 2009.Google Scholar
- R. Lipton and J. Naughton. Estimating the size of generalized transitive closures. In VLDB, pages 165--171, 1989. Google ScholarDigital Library
- M. Newman. A measure of betweenness centrality based on random walks. Social Networks, 27(1):39--54, 2005.Google ScholarCross Ref
- M. Ortiz, J. Hoyos, and M. Lopez. The social networks of academic performance in a student context of poverty in mexico. Social Networks, 26(2):175--188, 2004.Google ScholarCross Ref
- Y. Said, E. Wegman, W. Sharabati, and J. Rigsby. Social networks of author-coauthor relationships. Computational Statistics and Data Analysis, 52:2177--2184, 2008. Google ScholarDigital Library
- A. Sala, L. Cao, C. Wilson, R. Zablit, H. Zheng, and B. Zhao. Measurement-calibrated graph models for social network experiments. In WWW, pages 861--870, 2010. Google ScholarDigital Library
- B. Singh and N. Gupte. Congestion and decongestion in a communication network. Phys. Rev. E, 71(5):055103, 2005.Google ScholarCross Ref
- K. Stephenson and M. Zelen. Rethinking centrality: Methods and examples. Social Networks, 11:1--37, 1989.Google ScholarCross Ref
Index Terms
- K-path centrality: a new centrality measure in social networks
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