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A measure of authors’ centrality in co-authorship networks based on the distribution of collaborative relationships

Author

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  • Haiyang Lu

    (Harbin Institute of Technology
    National TPM Center of China)

  • Yuqiang Feng

    (Harbin Institute of Technology
    National TPM Center of China)

Abstract

Although there are many measures of centrality of individuals in social networks, and those centrality measures can be applied to the analysis of authors’ importance in co-authorship networks, the distribution of an author’s collaborative relationships among different communities has not been considered. This distribution or extensity is an important aspect of authors’ activity. In the present study, we will propose a new measure termed extensity centrality, taking into account the distribution of an author’s collaborative relationships. In computing the strength of collaborative ties, which is closely related to the extensity centrality, we choose Salton’s measure. We choose the ACM SIGKDD data as our testing data set, and analyze the result of authors’ importance from different points of view.

Suggested Citation

  • Haiyang Lu & Yuqiang Feng, 2009. "A measure of authors’ centrality in co-authorship networks based on the distribution of collaborative relationships," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(2), pages 499-511, November.
    • Handle: RePEc:spr:scient:v:81:y:2009:i:2:d:10.1007_s11192-008-2173-x
    DOI: 10.1007/s11192-008-2173-x
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    Cited by:

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    11. Sahatqija, Kosovare & Kadriu, Arbana, 2019. "Exploring Gender Role in Co-Authorship Networks for Computing Books: A Case Study in DBLP," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019, pages 33-39, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    12. Peter Mutschke & Philipp Mayr, 2015. "Science models for search: a study on combining scholarly information retrieval and scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2323-2345, March.
    13. Miloš Savić & Mirjana Ivanović & Bojana Dimić Surla, 2017. "Analysis of intra-institutional research collaboration: a case of a Serbian faculty of sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 195-216, January.
    14. Hildrun Kretschmer & Donald Beaver & Theo Kretschmer, 2015. "Three-dimensional visualization and animation of emerging patterns by the process of self-organization in collaboration networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 87-120, July.
    15. Li, Eldon Y. & Liao, Chien Hsiang & Yen, Hsiuju Rebecca, 2013. "Co-authorship networks and research impact: A social capital perspective," Research Policy, Elsevier, vol. 42(9), pages 1515-1530.
    16. Guijie Zhang & Luning Liu & Yuqiang Feng & Zhen Shao & Yongli Li, 2014. "Cext-N index: a network node centrality measure for collaborative relationship distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 291-307, October.
    17. Guan, JianCheng & Zuo, KaiRui & Chen, KaiHua & Yam, Richard C.M., 2016. "Does country-level R&D efficiency benefit from the collaboration network structure?," Research Policy, Elsevier, vol. 45(4), pages 770-784.
    18. Sabine Brunswicker & Sorin Adam Matei & Michael Zentner & Lynn Zentner & Gerhard Klimeck, 2017. "Creating impact in the digital space: digital practice dependency in communities of digital scientific innovations," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 417-442, January.
    19. Choong Kwai Fatt & Ephrance Abu Ujum & Kuru Ratnavelu, 2010. "The structure of collaboration in the Journal of Finance," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 849-860, December.
    20. Zewen Hu & Angela Lin & Peter Willett, 2019. "Identification of research communities in cited and uncited publications using a co-authorship network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 1-19, January.
    21. Peter Mutschke & Philipp Mayr & Philipp Schaer & York Sure, 2011. "Science models as value-added services for scholarly information systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 349-364, October.

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