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What we learn from the shifts in highly cited data from 2001 to 2014?

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  • John T. Li

    (The Wheatley School)

Abstract

Thomson Reuter’s highly cited database (HiCite) ( http://www.highlycited.com ) is composed of the top researchers in several subspecialties belonging to the 22 essential science indicator fields of the web of science. By analyzing the data collected, we are able to calculate several correlations in the data based upon select areas, view trends of changes in rank, percentage of contribution, and countries, and re-rank the organizations by new standards. The purpose of this is to refocus and highlight previously unaccounted but significant details that are historically ignored, such as economics, specialties, nationality, efficiency, and field, and to evaluate performance of the separate organizations by multiple factors, with an emphasis on the status of the United States of America.

Suggested Citation

  • John T. Li, 2016. "What we learn from the shifts in highly cited data from 2001 to 2014?," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 57-82, July.
    • Handle: RePEc:spr:scient:v:108:y:2016:i:1:d:10.1007_s11192-016-1958-6
    DOI: 10.1007/s11192-016-1958-6
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    References listed on IDEAS

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    1. Chen, Shiji & Arsenault, Clément & Larivière, Vincent, 2015. "Are top-cited papers more interdisciplinary?," Journal of Informetrics, Elsevier, vol. 9(4), pages 1034-1046.
    2. Eva Lillquist & Sheldon Green, 2010. "The discipline dependence of citation statistics," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 749-762, September.
    3. Alfredo Yegros-Yegros & Ismael Rafols & Pablo D’Este, 2015. "Does Interdisciplinary Research Lead to Higher Citation Impact? The Different Effect of Proximal and Distal Interdisciplinarity," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-21, August.
    4. D. Docampo & D. Egret & L. Cram, 2015. "The effect of university mergers on the Shanghai ranking," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 175-191, July.
    5. Lutz Bornmann & Johann Bauer, 2015. "Evaluation of the highly-cited researchers’ database for a country: proposals for meaningful analyses on the example of Germany," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1997-2003, December.
    6. C. Malesios & S. Psarakis, 2014. "Comparison of the h-index for different fields of research using bootstrap methodology," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 521-545, January.
    7. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
    8. Wolfgang Glänzel & András Schubert, 2003. "A new classification scheme of science fields and subfields designed for scientometric evaluation purposes," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(3), pages 357-367, March.
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    Cited by:

    1. Hanna Hottenrott & Cornelia Lawson, 2022. "What is behind multiple institutional affiliations in academia?," Science and Public Policy, Oxford University Press, vol. 49(3), pages 382-402.
    2. Lutz Bornmann & Johann Bauer & Elisabeth Maria Schlagberger, 2017. "Characteristics of highly cited researchers 2015 in Germany," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 543-545, April.

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