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How is an academic social site populated? A demographic study of Google Scholar Citations population

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  • José Luis Ortega

    (CCHS-CSIC)

Abstract

This paper intends to describe the population evolution of a scientific information web service during 2011–2012. Quarterly samples from December 2011 to December 2012 were extracted from Google Scholar Citations to analyse the number of members, distribution of their bibliometric indicators, positions, institutional and country affiliations and the labels to describe their scientific activity. Results show that most of the users are young researchers, with a starting scientific career and mainly from disciplines related to information sciences and technologies. Another important result is that this service is settled by waves emanating from specific institutions and countries. This work concludes that this academic social network presents some biases in the population distribution that does not make it representative of the real scientific population.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:104:y:2015:i:1:d:10.1007_s11192-015-1593-7
    DOI: 10.1007/s11192-015-1593-7
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    References listed on IDEAS

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    1. José Luis Ortega & Isidro F. Aguillo, 2014. "Microsoft academic search and Google scholar citations: Comparative analysis of author profiles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(6), pages 1149-1156, June.
    2. Mike Thelwall & Kayvan Kousha, 2014. "Academia.edu: Social network or Academic Network?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 721-731, April.
    3. Henk F. Moed, 2005. "Statistical relationships between downloads and citations at the level of individual documents within a single journal," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(10), pages 1088-1097, August.
    4. Niamh M. Hogan & Karl J. Sweeney, 2013. "Social networking and scientific communication: A paradoxical return to Mertonian roots?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(3), pages 644-646, March.
    5. José Luis Ortega & Isidro F. Aguillo, 2012. "Science is all in the eye of the beholder: Keyword maps in Google scholar citations," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2370-2377, December.
    6. Filippo Radicchi & Claudio Castellano, 2013. "Analysis of bibliometric indicators for individual scholars in a large data set," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 627-637, December.
    7. Amalia Mas-Bleda & Mike Thelwall & Kayvan Kousha & Isidro F. Aguillo, 2014. "Do highly cited researchers successfully use the social web?," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 337-356, October.
    8. Isidro F. Aguillo, 2012. "Is Google Scholar useful for bibliometrics? A webometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 343-351, May.
    9. Xuemei Li & Mike Thelwall & Dean Giustini, 2012. "Validating online reference managers for scholarly impact measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 461-471, May.
    10. Stefanie Haustein & Isabella Peters & Judit Bar-Ilan & Jason Priem & Hadas Shema & Jens Terliesner, 2014. "Coverage and adoption of altmetrics sources in the bibliometric community," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1145-1163, November.
    11. M. Ryan Haley, 2014. "Ranking top economics and finance journals using Microsoft academic search versus Google scholar: How does the new publish or perish option compare?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1079-1084, May.
    12. Staša Milojević, 2010. "Power law distributions in information science: Making the case for logarithmic binning," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2417-2425, December.
    13. José Luis Ortega & Isidro F. Aguillo, 2012. "Science is all in the eye of the beholder: Keyword maps in Google scholar citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2370-2377, December.
    14. Emilio Delgado López-Cózar & Nicolás Robinson-García & Daniel Torres-Salinas, 2014. "The Google scholar experiment: How to index false papers and manipulate bibliometric indicators," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(3), pages 446-454, March.
    15. Ortega, José Luis & Aguillo, Isidro F., 2013. "Institutional and country collaboration in an online service of scientific profiles: Google Scholar Citations," Journal of Informetrics, Elsevier, vol. 7(2), pages 394-403.
    16. Lokman I. Meho & Kiduk Yang, 2007. "Impact of data sources on citation counts and rankings of LIS faculty: Web of science versus scopus and google scholar," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(13), pages 2105-2125, November.
    17. Niamh M. Hogan & Karl J. Sweeney, 2013. "Social networking and scientific communication: A paradoxical return to Mertonian roots?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(3), pages 644-646, March.
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    1. Martín-Martín, Alberto & Orduna-Malea, Enrique & Delgado López-Cózar, Emilio, 2018. "Author-level metrics in the new academic profile platforms: The online behaviour of the Bibliometrics community," Journal of Informetrics, Elsevier, vol. 12(2), pages 494-509.
    2. 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.
    3. Alberto Martín-Martín & Enrique Orduna-Malea & Emilio Delgado López-Cózar, 2018. "A novel method for depicting academic disciplines through Google Scholar Citations: The case of Bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1251-1273, March.
    4. Matveeva, Nataliya & Poldin, Oleg, 2016. "Citation of scholars in co-authorship network: Analysis of Google Scholar data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 44, pages 100-118.
    5. Margaret K. Merga & Sayidi Mat Roni & Shannon Mason, 2020. "Should Google Scholar be used for benchmarking against the professoriate in education?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2505-2522, December.
    6. Basma Albanna & Julia Handl & Richard Heeks, 2021. "Publication outperformance among global South researchers: An analysis of individual-level and publication-level predictors of positive deviance," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8375-8431, October.

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