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Citation of scholars in co-authorship network: Analysis of Google Scholar data


  • Matveeva, Nataliya

    () (National Research University Higher School of Economics, Nizhny Novgorod, Russian Federation)

  • Poldin, Oleg

    () (National Research University Higher School of Economics, Saint Petersburg, Russian Federation)


In this study, we analyze correlations between the co-authorship network parameters and citation characteristics in Google Scholar. We estimate the count data regression model in a sample of more than 30 thousand authors with the first citation after 2007. There is a positive relationship between scholar’s citation counts and number of co-authors, between citations and the author’s centrality, and between scholar’s citations and the average citation of co-authors. The h-index and i10 index are significantly associated with the number of co-authors and average citation of co-authors.

Suggested Citation

  • Matveeva, Nataliya & Poldin, Oleg, 2016. "Citation of scholars in co-authorship network: Analysis of Google Scholar data," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 44, pages 100-118.
  • Handle: RePEc:ris:apltrx:0306

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    References listed on IDEAS

    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273.
    2. 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.
    3. Lorenzo Ductor & Marcel Fafchamps & Sanjeev Goyal & Marco J. van der Leij, 2014. "Social Networks and Research Output," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 936-948, December.
    4. 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.
    5. Fooladi, Masood & Salehi, Hadi & Md Yunus, Melor & Farhadi, Maryam & Aghaei Chadegani, Arezoo & Farhadi, Hadi & Ale Ebrahim, Nader, 2013. "Does Criticisms Overcome the Praises of Journal Impact Factor?," MPRA Paper 46899, University Library of Munich, Germany, revised 18 Mar 2013.
    6. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    7. Ajiferuke, Isola & Famoye, Felix, 2015. "Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models," Journal of Informetrics, Elsevier, vol. 9(3), pages 499-513.
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    More about this item


    scientometrics; co-authorship network; bibliometric analysis; Google Scholar; count data models.;

    JEL classification:

    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification


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