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A measure of reliability for scientific co-authorship networks using fuzzy logic

Author

Listed:
  • Sandra Cristina Oliveira

    (São Paulo State University – UNESP)

  • Juliana Cobre

    (Universidade de São Paulo – USP)

  • Danilo Florentino Pereira

    (São Paulo State University – UNESP)

Abstract

Studies on the reliability of scientific co-authorship networks identify whether they are reliable, according to their researchers’ participation and how strong the co-authorship relationships are. Co-authorship among members of a research group can usually be represented by a graph in which each node represents one of the researchers belonging to this group, and each edge represents a connection (co-authorship relationship) between two researchers. The aim of this investigation is to propose a mathematical analysis using fuzzy logic to estimate the reliability of scientific co-authorship networks, based on node centrality measures and the existence of uncertainties in estimating the reliability of the individual components (researchers). To develop the proposed methodology, a research group from São Paulo State University–UNESP registered with the National Council for Scientific and Technological Development (CNPq) in Brazil was analysed. The results show the simplicity of implementation and the viability of mathematical modelling to estimate the reliability of scientific co-authorship networks.

Suggested Citation

  • Sandra Cristina Oliveira & Juliana Cobre & Danilo Florentino Pereira, 2021. "A measure of reliability for scientific co-authorship networks using fuzzy logic," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4551-4563, June.
  • Handle: RePEc:spr:scient:v:126:y:2021:i:6:d:10.1007_s11192-021-03915-0
    DOI: 10.1007/s11192-021-03915-0
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    References listed on IDEAS

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    1. Jian Wang & Kaspars Berzins & Diana Hicks & Julia Melkers & Fang Xiao & Diogo Pinheiro, 2012. "A boosted-trees method for name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 391-411, November.
    2. Alireza Abbasi & Jörn Altmann & Junseok Hwang, 2010. "Evaluating scholars based on their academic collaboration activities: two indices, the RC-index and the CC-index, for quantifying collaboration activities of researchers and scientific communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 1-13, April.
    3. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    4. Dehdarirad, Tahereh & Nasini, Stefano, 2017. "Research impact in co-authorship networks: a two-mode analysis," Journal of Informetrics, Elsevier, vol. 11(2), pages 371-388.
    5. Abbasi, Alireza & Altmann, Jörn & Hossain, Liaquat, 2011. "Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures," Journal of Informetrics, Elsevier, vol. 5(4), pages 594-607.
    6. Haeussler, Carolin & Sauermann, Henry, 2013. "Credit where credit is due? The impact of project contributions and social factors on authorship and inventorship," Research Policy, Elsevier, vol. 42(3), pages 688-703.
    7. Tahereh Dehdarirad & Stefano Nasini, 2017. "Research impact in co-authorship networks: a two-mode analysis," Post-Print hal-01745330, HAL.
    8. Erjia Yan & Ying Ding, 2009. "Applying centrality measures to impact analysis: A coauthorship network analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 2107-2118, October.
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