Abstract
How to evaluate the importance of nodes in networks and detect the centrality has become a vital problem in improving the efficiency of telecommunication and making a disease immunity strategy. We consider the mechanisms of real networks, and define a cost function to describe different hierarchies of networks to measure node importance. This method takes up a node’s regional influence as well as its global influence to evaluate its importance. The results of simulation prove that this method is proper to describe effectively and detect node discrepancies in a network.
Similar content being viewed by others
References
Watts D, Strogatz S. Collective dynamics of small-world networks. Nature, 1998, 393(6684): 440–442
Albert R, Jeong H, Barabas A L. Error and attack tolerance of complex networks. Nature, 2000, 406: 378–382
Barabasi A L, Albert R. Emergence of scaling in random networks. Science, 1999, 286(5439): 509–512
Albert R, Jeong H, Barabasi A L. Diameter of the world-wide web. Nature, 1999, 401: 130–131
Albert R, Barabasi A L. Statistical mechanics of complex networks. Reviews of Modern Physics, 2002, 74: 47–97
Newman M. The structure and function of complex networks. SIAM Review, 2003, 45: 167–256
Goh K, Oh E, Kahng B, Kim D. Betweenness centrality correlation in social networks. Physical Review E, 2003, 67: 017101
Albert R, Barabasi A L. Topology of evolving networks: local events and university. Physical Review Letters, 2000, 85(24): 5234–5237
Freeman L. A set of measures of centrality based upon betweenness. Sociometry, 1977, 40(1): 35–41
Freeman L. Centrality in social networks: conceptual clarification. Social Networks, 1979, 1(3): 215–219
Freeman L, Roeder D, Mulholland R R. Centrality in social networks: ii. experimental results. Social Networks, 1979, 2: 119–141
Brandes U. A fast algorithm for betweenness centrality. Journal of Mathematical Sociology, 2001, 25(2): 163–171
Estrada E, Rodriguez-Velazquez J A. Subgraph centrality in complex networks. Physical Review E, 2005, 71: 056103
Newman M. A measure of betweenness centrality based on random walk. Social Networks, 2005, 27(1): 39–54
Klovdahl A S. Social networks and the spread of infectious diseases: the AIDS example. Social Science & Medicine, 1985, 21(11): 1203–1216
Barthelemy M. Betweenness centrality in large complex networks. The European Physical Journal B, 2004, 38(2): 163–168
Tan Y J, Wu J, Deng H Z. Evaluation method for node importance based on node contraction in complex networks. System Engineering-Theory & Practice, 2006, (11): 26–35
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rong, L., Guo, T. & Zhang, J. A new centrality measure based on sub-tree. Front. Comput. Sci. China 3, 356–360 (2009). https://doi.org/10.1007/s11704-009-0046-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11704-009-0046-y