The brittleness analysis and important nodes detection have been a hot spot in the complex networks.
How to get the overall feature of the whole network and how to find out some important nodes are requisites to
solve these problems. In this paper, we adopt the trace of the adjacency matrix and the centrality of the complex
networks to give a quantitative and qualitative analysis of networks being studied. Results show that the k-shell
plays a more important role than the degree centrality and the betweenness in finding important nodes, and it
can also be used to give direction on the immunization and maintenance of complex networks.
ZHANG Honga* (张 红), HU Changzhenb (胡昌振), WANG Xiaojuna (王小军)
. Brittleness Analysis and Important Nodes Discovery in Large Time-Evolving Complex Networks[J]. Journal of Shanghai Jiaotong University(Science), 2017
, 22(1)
: 50
-054
.
DOI: 10.1007/s12204-017-1798-4
[1] LI X, CHEN G R. A local-world evolving networkmodel [J]. Physica A, 2003, 328(1): 274-286.
[2] BARRAT A, BARTH′ELEMY M, VESPIGNANI A.Weighted evolving networks: Coupling topology andweight dynamics [J]. Physicals Review Letters, 2004,92(22): 228701.
[3] SHETTY J, ADIBI J. Discovering important nodesthrough graph entropy: The case of enron emaildatabase [C]//Proceedings of the 3rd InternationalWorkshop on Link Discovery. Chicage, USA: ACM,2005: 74-81.
[4] AKOGLU L. Mining and modeling real-world networks:Patterns, anomalies, and tools [D]. Pittsburgh,PA: School of Computer Science, Carnegie Mellon University,2012.
[5] BORGATTI S P. Identifying sets of key players in asocial network [J]. Computational and MathematicalOrganization Theory, 2006, 12: 21-34.
[6] PITTEL B, SPENCER J, WORMALD N. Suddenemergence of a giant k-core in a random graph [J].Journal of Combinatorial Theory, Series B, 1996, 67:111-151.
[7] CARMI S, HAVLIN S, KIRKPATRICK S, et al. Amodel of Internet topology using k-shell decomposition[J]. Proceedings of the National Academy of Sciences ofthe United States of America, 2007, 104(27): 11150-11154.
[8] REN Z M, LIU J G, SHAO F, et al. Analysis of thespreading influence of the nodes with minimum K-shellvalue in complex networks [J]. Acta Physica Sinica,2013, 62(10): 466-471 (in Chinese).
[9] GAO J, LIANG F, FAN W, et al. On communityoutliers and their efficient detection in informationnetworks [C]//Proceedings of International Conferenceon Knowledge Discovery & Data Mining. Washington,USA: ACM, 2010: 813-822.
[10] YOSHINOBU K, YAIRI T, MACHIDA K. Changepointdetection in time-series data based on subspaceidentification [C]//Proceedings of the 2007 SeventhIEEE International Conference on Data Mining. Omaha,USA: IEEE, 2007: 559-564.
