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How Network Characteristics of Researchers Relate to Their Citation Indicators – a Co-Authorship Network Analysis Based on Google Scholar

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  • Nataliya N. Matveeva

    (National Research University Higher School of Economics)

  • Oleg V. Poldin

    (National Research University Higher School of Economics)

Abstract

The most common quantitative estimates of scientific performance are based on citation indices, and it is meaningful to identify what affects these indicators. In this work, we analyze the correlations between the citation characteristics of researchers and their co-authorship network parameters, which indicate the position of scientists in an academic network. To surpass the shortcoming of previous works we use a large sample and separate researchers by the year of their first citation. For constructing a co-authorship network, we used data about researchers from different disciplines, who have profiles in Google Scholar. The results of a count data regression model indicate that citations positively correlate with the number of co-authors, with position of the researcher in the co-authorship network (closeness centrality), and with the average number of co-author' citation. Also we reveal that the h-index and the i10-index are significantly associated with the number of co-authors and the average number of co-author citations. Based on these results, we can conclude that researchers who maintain more contacts and are more active than others have better bibliometric indicators on the average

Suggested Citation

  • Nataliya N. Matveeva & Oleg V. Poldin, 2017. "How Network Characteristics of Researchers Relate to Their Citation Indicators – a Co-Authorship Network Analysis Based on Google Scholar," HSE Working papers WP BRP 44/EDU/2017, National Research University Higher School of Economics.
  • Handle: RePEc:hig:wpaper:44edu2017
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    References listed on IDEAS

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    1. Martin-Martin, Alberto & Orduna-Malea, Enrique & Harzing, Anne-Wil & Delgado López-Cózar, Emilio, 2017. "Can we use Google Scholar to identify highly-cited documents?," Journal of Informetrics, Elsevier, vol. 11(1), pages 152-163.
    2. Guan, Jiancheng & Yan, Yan & Zhang, Jing Jing, 2017. "The impact of collaboration and knowledge networks on citations," Journal of Informetrics, Elsevier, vol. 11(2), pages 407-422.
    3. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, January.
    4. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    5. 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.
    6. Poovanalingam Murugesan & Michael J. Moravcsik, 1978. "Variation of the nature of citation measures with journals and scientific specialties," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 29(3), pages 141-147, May.
    7. 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.
    8. Hanna-Mari Puuska & Reetta Muhonen & Yrjö Leino, 2014. "International and domestic co-publishing and their citation impact in different disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 823-839, February.
    9. 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.
    10. Necmi K. Avkiran, 2013. "An empirical investigation of the influence of collaboration in Finance on article impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 911-925, June.
    11. Jevin West & Theodore Bergstrom & Carl T. Bergstrom, 2010. "Big Macs and Eigenfactor scores: Don't let correlation coefficients fool you," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(9), pages 1800-1807, September.
    12. José Luis Ortega, 2015. "How is an academic social site populated? A demographic study of Google Scholar Citations population," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 1-18, July.
    13. Cimenler, Oguz & Reeves, Kingsley A. & Skvoretz, John, 2014. "A regression analysis of researchers’ social network metrics on their citation performance in a college of engineering," Journal of Informetrics, Elsevier, vol. 8(3), pages 667-682.
    14. 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.
    15. Costas, Rodrigo & Bordons, María, 2007. "The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level," Journal of Informetrics, Elsevier, vol. 1(3), pages 193-203.
    16. Lorna Wildgaard, 2015. "A comparison of 17 author-level bibliometric indicators for researchers in Astronomy, Environmental Science, Philosophy and Public Health in Web of Science and Google Scholar," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 873-906, September.
    17. Olle Persson & Wolfgang Glänzel & Rickard Danell, 2004. "Inflationary bibliometric values: The role of scientific collaboration and the need for relative indicators in evaluative studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 421-432, August.
    18. 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

    Keywords

    co-authorship network; bibliometric analysis; Google Scholar; count data models;
    All these keywords.

    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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