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

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.

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References

  • Aguillo, I. F. (2012). Is Google Scholar useful for bibliometrics? A webometric analysis. Scientometrics, 91(2), 343–351.

    Article  Google Scholar 

  • Almousa, O. (2011). Users’ classification and usage-pattern identification in academic social networks. In IEEE Jordan conference on applied electrical engineering and computing technologies AEECT (pp 1–6). New York: IEEE.

  • Bakkalbasi, N., Bauer, K., Glover, J., & Wang, L. (2006). Three options for citation tracking: Google Scholar, Scopus and Web of Science. Biomedical Digital Libraries, 3, 7. http://www.bio-diglib.com/content/3/1/7

  • Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230.

    Article  Google Scholar 

  • Chakraborty, N. (2012). Activities and reasons for using social networking sites by research Scholars in NEHU: A study on Facebook and ResearchGate. 8th convention PLANNER-2012, Sikkim University, Gangtok. Ahmedabad, IN: IFLIBNET. Retrieved from http://ir.inflibnet.ac.in/bitstream/handle/1944/1666/3.pdf?sequence=1

  • Chang, J., Rosenn, I., Backstrom, L., & Marlow, C. (2010). ePluribus: Ethnicity on social networks. In Fourth international conference on weblogs and social media (ICWSM-10). Washington DC: AAAI Press.

  • Delgado López-Cózar, E., Robinson-García, N., & Torres-Salinas, D. (2014). The Google scholar experiment: How to index false papers and manipulate bibliometric indicators. Journal of the Association for Information Science and Technology, 65(3), 446–454.

    Article  Google Scholar 

  • Duggan, M., & Smith, A. (2013). Social media update 2013. Washington DC: Pew Research Center. Retrieved from http://pewinternet.org/Reports/2013/Social-Media-Update.aspx

  • Ebner, M., & Reinhardt, W. (2009). Social networking in scientific conferences—Twitter as tool for strengthen a scientific community. In 4th European conference on technology enhanced learning, EC-TEL 2009. Nice: Springer.

  • Eysenbach, G. (2011). Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13(4), e123.

    Article  Google Scholar 

  • Garcia, D., Mavrodiev, P., & Schweitzer, F. (2013). Social resilience in online communities: The autopsy of Friendster. Retrieved from http://arxiv.org/pdf/1302.6109.pdf

  • Glänzel, W., & Heeffer, S. (2014). Cross-national preferences and similarities in downloads and citations of scientific articles: A pilot study. In Proceedings of the science and technology indicators conference. Leiden: Universiteit Leiden.

  • Google Refine. (2015). Google Refine, a power tool for working with messy data (formerly Freebase Gridworks): Google Project Hosting. https://code.google.com/p/google-refine/

  • Halevi, G., & Moed, H. (2014). Usage patterns of scientific journals and their relationship with citations. In Proceedings of the science and technology indicators conference. Leiden: Universiteit Leiden.

  • Haley, M. R. (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 and Technology, 65(5), 1079–1084.

  • Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Shema, H., & Terliesner, J. (2014). Coverage and adoption of altmetrics sources in the bibliometric community. Scientometrics. doi:10.1007/s11192-013-1221-3.

    MATH  Google Scholar 

  • Hogan, N. M., & Sweeney, K. J. (2013). Social networking and scientific communication: A paradoxical return to Mertonian roots? Journal of the American Society for Information Science and Technology, 64(3), 644–646.

    Article  Google Scholar 

  • Huang, Z., & Yuan, B. (2012). Mining Google Scholar Citations: An exploratory study. Lecture Notes in Computer Science, 7389, 182–189.

    Google Scholar 

  • Jacsó, P. (2008). Google Scholar revisited. Online Information Review, 32(1), 102–114.

    Article  Google Scholar 

  • Kousha, K., & Thelwall, M. (2007). Google Scholar Citations and Google Web-URL citations: A multi-discipline exploratory analysis. Journal of the American Society for Information Science and Technology, 58(7), 1055–1065.

    Article  Google Scholar 

  • Li, X., Thelwall, M., & Giustini, D. (2012). Validating online reference managers for scholarly impact measurement. Scientometrics, 91(2), 461–471.

    Article  Google Scholar 

  • Mas-Bleda, A., Thelwall, M., Kousha, K., & Aguillo, I. F. (2014). Do highly cited researchers successfully use the social web? Scientometrics,. doi:10.1007/s11192-014-1345-0.

    Google Scholar 

  • Meho, L. I., & Yang, K. (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, 58(13), 2105–2125.

    Article  Google Scholar 

  • Mendeley. (2012). Global research report. Retrieved from http://www.mendeley.com/global-research-report/#.UsbnMLQ5s4M

  • Menendez, M., de Angeli, A., & Menestrina, Z. (2012). Exploring the virtual space of academia. In J. Dugdale, et al. (Eds.), From research to practice in the design of cooperative systems: Results and open challenges. London: Springer.

    Google Scholar 

  • Milojević, S. (2010). Power law distributions in information science: Making the case for logarithmic binning. Journal of the American Society for Information Science and Technology, 61(12), 2417–2425.

    Article  Google Scholar 

  • Mislove, A., Lehmann, S., Ahn, Y. Y., Onnela, J. P., & Rosenquist, J. N. (2011). Understanding the demographics of Twitter users. In 5th international AAAI conference on weblogs and social media (pp 554–557). Barcelona: AAAI Press.

  • Moed, H. F. (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, 56(10), 1088–1097.

    Article  Google Scholar 

  • Ortega, J. L. (2014). Academic search engines: A quantitative outlook (p 200). Cambridge: Chandos Publishing. ISBN:1843347911.

  • Ortega, J. L., & Aguillo, I. F. (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, 63(12), 2370–2377.

    Article  Google Scholar 

  • Ortega, J. L., & Aguillo, I. F. (2013). Institutional and country collaboration in an online service of scientific profiles: Google Scholar Citations. Journal of Informetrics, 7(2), 394–403.

    Article  Google Scholar 

  • Ortega, J. L., & Aguillo, I. F. (2014). Microsoft academic search and Google scholar citations: A comparative analysis of author profiles. Journal of the American Society for Information Science and Technology, 65(6), 1149–1156.

  • Pitney, W. A., & Gilson, T. A. (2012). Educational technology: Using Google Scholar Citations to support the impact of scholarly work. Athletic Training Education Journal, 7(1), 38–39.

    Article  Google Scholar 

  • Radicchi, F., & Castellano, C. (2013). Analysis of bibliometric indicators for individual scholars in a large data set. Scientometrics, 97(3), 627–637.

    Article  Google Scholar 

  • ResearchGate. (2014). Main page. Retrieved from http://www.researchgate.net/.

  • Seber, G. A. F. (2002). The estimation of animal abundance and related parameters. Caldwel, NJ: Blackburn Press.

    Google Scholar 

  • Shneiderman, B. (2008). Science 2.0. Science, 319(5868), 1349–1350.

    Article  Google Scholar 

  • Thelwall, M., & Kousha, K. (2014). Academia.edu: Social network or academic network? Journal of the Association for Information Science and Technology, 65(4), 721–731.

    Article  Google Scholar 

  • Tilling, K. (2001). Capture–recapture methods—Useful or misleading? International Journal of Epidemiology, 30(1), 12–14.

    Article  Google Scholar 

  • Van Eperen, L., & Marincola, F. M. (2011). How scientists use social media to communicate their research. Journal of Translational Medicine, 9(1), 1–3.

    Article  Google Scholar 

  • Watson, A. B. (2009). Comparing citations and downloads for individual articles at the Journal of Vision. Journal of Vision, 9(4), article i. Retrieved from http://www.journalofvision.org/content/9/4/i.

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Acknowledgments

I would like to thank Jennifer Carranza her helpful recommendations on the English version of this paper and the interesting suggestions of the reviewers.

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Correspondence to José Luis Ortega.

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Ortega, J.L. How is an academic social site populated? A demographic study of Google Scholar Citations population. Scientometrics 104, 1–18 (2015). https://doi.org/10.1007/s11192-015-1593-7

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Keywords

  • Web bibliometrics
  • Google Scholar Citations
  • Academic social networks
  • Web demography