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New Technology of Library and Information Service  2012, Vol. 28 Issue (5): 65-69    DOI: 10.11925/infotech.1003-3513.2012.05.10
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Influential Spreaders in Co-author Network Based on K-shell
Zhang Jinzhu
National Science Library, Chinese Academy of Sciences, Beijing 100190, China; Graduate University of Chinese Academy of Sciences, Beijing 100049, China
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Abstract  Based on the data comes from 12 journals between 2000-2009 which contains 7 389 different authors,this paper computes the degree, betweenness centrality and K-shell and makes a comparative analysis. The results show that K-shell does better in identification of influential spreaders in co-author network. This method can be also used in co-citation network and coupling network for identification of influential spreaders.
Key wordsInfluential spreaders      Co-author network      K-shell      Degree      Betweenness centrality     
Received: 10 May 2012      Published: 24 July 2012



Cite this article:

Zhang Jinzhu. Influential Spreaders in Co-author Network Based on K-shell. New Technology of Library and Information Service, 2012, 28(5): 65-69.

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[1] Albert R, Jeong H, Barabási A L. Error and Attack Tolerance of Complex Networks[J]. Nature, 2000, 406(6794): 378-382.

[2] Cohen R, Erez K,Avraham D B,et al. Breakdown of the Internet Under Intentional Attack[J]. Physical Review Letters, 2001, 86(16): 3682-3685.

[3] Freeman L C. Centrality in Social Networks Conceptual Clarification[J]. Social Networks, 1979, 1(3): 215-239.

[4] Kitsak M, Gallos L K, Havlin S,et al. Identification of Influential Spreaders in Complex Networks[J]. Nature Physics, 2010, 6(11): 888-893.

[5] White H D, McCain K W. Visualizing a Discipline: An Author Co-citation Analysis of Information Science, 1972-1995[J]. Journal of the American Society for Information Science, 1998, 49(4): 327-355.

[6] Zhao D Z, Strotmann A. Evolution of Research Activities and Intellectual Influences in Information Science 1996-2005: Introducing Author Bibliographic-Coupling Analysis[J]. Journal of the American Society for Information Science and Technology, 2008, 59(13): 2070-2086.

[7] Chen C M, Ibekwe-SanJuan F, Hou J H. The Structure and Dynamics of Cocitation Clusters: A Multiple-Perspective Cocitation Analysis[J]. Journal of the American Society for Information Science and Technology, 2010, 61(7): 1386-1409.

[8] 张金柱. 情报学的学科结构及其演化分析[J]. 情报资料工作 , 2011(3): 34-37.(Zhang Jinzhu.An Analysis of the Disciplinary Structure and Evolution of Information Science[J]. Information and Documentation Services,2011(3):34-37)

[9] Newman M E J. The Structure and Function of Complex Networks[J]. SIAM Review, 2003, 45(2): 167-256.

[10] Pastor-Satorras R, Vespignani A. Immunization of Complex Networks[J]. Physical Review E, 2002, 65(3): 036104.

[11] Lloyd A L, May R M. How Viruses Spread Among Computers and People[J]. Science, 2001, 292(5520): 1316.

[12] Pastor-Satorras R, Vespignani A. Epidemic Spreading in Scale-free Networks[J]. Physical Review Letters, 2001, 86(14): 3200-3203.

[13] Chen C. Searching for Intellectual Turning Points: Progressive Knowledge Domain Visualization[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(S1): 5303.

[14] Chen C. Predictive Effects of Structural Variation on Citation Counts[J]. Journal of the American Society for Information Science and Technology, 2011,63(3): 431-449.

[15] Friedkin N E. Theoretical Foundations for Centrality Measures[J]. American Journal of Sociology, 1991,96(6):1478-1504.

[16] Daley D J, Gani J, Gani J M. Epidemic Modelling: an Introduction[M]. NY: Cambridge University Press, 2001.
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