Cext-N index: a network node centrality measure for collaborative relationship distribution

Abstract

This paper focuses on methods to study the distribution of an author’s collaborative relationships among different communities in co-authorship networks. Based on the index of extensity centrality, we propose a new index and name it extensity centrality-Newman (Cext-N). Drawing upon a data set of three top journals (MISQ, ISR, JMIS) between 2010 and 2012 in Information Systems, we verify and describe the application and value of our approach. Due to the fact that the starting points among Cext-N and classical indices are quite different and a single index is not advocated in scientific evaluation, we can select the indices in actual application by considering their starting points to ensure the value of each index is taken into account.

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Acknowledgments

This work is partly supported by the National Natural Science Foundation of PRC (Nos. 71172157, 71201039, 71371059 and 71301035) and a grant from the Postdoctoral Science Foundation of China (#2014M550198), and the Fundamental Research Funds for the Central Universities (Grant No. HIT. HSS. 201205).

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Correspondence to Guijie Zhang or Luning Liu.

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Zhang, G., Liu, L., Feng, Y. et al. Cext-N index: a network node centrality measure for collaborative relationship distribution. Scientometrics 101, 291–307 (2014). https://doi.org/10.1007/s11192-014-1358-8

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Keywords

  • Centrality measure
  • Co-authorship network
  • Collaborative relationship distribution
  • Lambda sets
  • Community