Please wait a minute...
New Technology of Library and Information Service  2010, Vol. 26 Issue (5): 66-72    DOI: 10.11925/infotech.1003-3513.2010.05.11
article Current Issue | Archive | Adv Search |
Analysis of Author’s Extensity Centrality in Co-authorship Networks in the Field of Management Information Systems
Li Lirong1,Qian Wei2,Feng Yuqiang1
1 (School of Management, Harbin Institute of Technology, Harbin 150001, China)
2 (School of Management, Agricultural University in Harbin, Harbin 150001, China)
Download: PDF(995 KB)   HTML  
Export: BibTeX | EndNote (RIS)      

Based on the concept and calculation method of extensity centrality, which are newly proposed in 2009, the paper builds co-authorship networks by the data of the world’s top three journals in Management Information Systems(MIS)field, analyzes the components of networks and calculates the extensity centrality of authors in five components. Then, it surveys and analyzes the backgrounds and cooperators’ research fields of those authors whose extensity centrality scores are high. The results indicate that the whole cooperative behavior of researchers in MIS is more active.Many of the authors with high extensity centrality scores are well-known experts or scholars in MIS, and they cooperate with scholars coming from various fields. Therefore,extensity centrality can indeed be used to evaluate the importance of experts and scholars.

Key wordsCo-authorship networks         Centrality         Extensity centrality     
Received: 12 April 2010      Published: 25 May 2010


Corresponding Authors: Trista Lee     E-mail:

Cite this article:

Li Lirong Qian Wei Feng Yuqiang. Analysis of Author’s Extensity Centrality in Co-authorship Networks in the Field of Management Information Systems. New Technology of Library and Information Service, 2010, 26(5): 66-72.

URL:     OR

[1] Kretschmer H. Patterns of Behavior in Co-authorship Networks of Invisible Colleges[J]. Scientometrics, 1997, 40(3): 579-591.
[2] Borner K, Dall’asta L, Ke W, et al. Studying the Emerging Global Brain:Analyzing and Visualizing the Impact of Co-authorship Teams[J].Complexity, 2005, 10(4): 57-67.
[3] Newman M E J. Scientific Collaboration Networks. I. Network Construction and Fundamental Results[J]. Physical Review E, 2001, 64(1):016131.
[4] Freeman C L. Centrality in Networks: Conceptual Clarification[J].Social Networks, 1979, 1(3): 215-239.
[5] Bonacich P. Factoring and Weighting Approaches to Status Scores and Clique  Identification[J].Journal of Mathematical Sociology, 1972, 2(1): 113-120.
[6] Brin S, Page L. The Anatomy of a Large-scale Hyper Textual Web Search Engine[C].In: Proceedings of the 7th ACM-WWW International Conference. Brisbane: ACM Press, 1998:107-117.
[7] Lu H Y, Feng Y Q. A Measure of Authors’ Centrality in Co-authorship Networks Based on the Distribution of Collaborative Relationships[J]. Scientometrics, 2009, 81(2):499-511.
[8] Newman M E J. The Structure of Scientific Collaboration Networks[C]. In:Proceedings of the National Academy of Sciences. 2001: 404-409.
[9] Luukkonen T, Tijssen R J W, Persson O, et al. The Measurement of International Scientific Collaboration[J]. Scientometrics,1993, 28(1): 15-36.
[10] Shannon C E. A Mathematical Theory of Communication[J]. The Bell System Technical Journal,1948,27: 379-423, 623-656.

[1] Sun Wenjun Wang Qian. Research on Discrimination of Scientific Papers Based on Laplacian Spectrum Analysis[J]. 现代图书情报技术, 2010, 26(5): 58-65.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938