IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v108y2016i1d10.1007_s11192-016-1958-6.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-016-1958-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-016-1958-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eva Lillquist & Sheldon Green, 2010. "The discipline dependence of citation statistics," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 749-762, September.
    2. 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.
    3. Chen, Shiji & Arsenault, Clément & Larivière, Vincent, 2015. "Are top-cited papers more interdisciplinary?," Journal of Informetrics, Elsevier, vol. 9(4), pages 1034-1046.
    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. 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.
    6. 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.
    7. 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.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shiji Chen & Yanhui Song & Fei Shu & Vincent Larivière, 2022. "Interdisciplinarity and impact: the effects of the citation time window," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2621-2642, May.
    2. Wolfgang Glänzel & Koenraad Debackere, 2022. "Various aspects of interdisciplinarity in research and how to quantify and measure those," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5551-5569, September.
    3. Javier Ruiz-Castillo, 2012. "The evaluation of citation distributions," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(1), pages 291-310, March.
    4. Wang, Jian & Veugelers, Reinhilde & Stephan, Paula, 2017. "Bias against novelty in science: A cautionary tale for users of bibliometric indicators," Research Policy, Elsevier, vol. 46(8), pages 1416-1436.
    5. Fei Shu & Jesse David Dinneen & Shiji Chen, 2022. "Measuring the disparity among scientific disciplines using Library of Congress Subject Headings," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3613-3628, June.
    6. Wei, Shelia X. & Tong, Tong & Rousseau, Ronald & Wang, Wanru & Ye, Fred Y., 2022. "Relations among the h-, g-, ψ-, and p-index and offset-ability," Journal of Informetrics, Elsevier, vol. 16(4).
    7. Frank J. Rijnsoever & Laurens K. Hessels, 2021. "How academic researchers select collaborative research projects: a choice experiment," The Journal of Technology Transfer, Springer, vol. 46(6), pages 1917-1948, December.
    8. Xiaojing Cai & Xiaozan Lyu & Ping Zhou, 2023. "The relationship between interdisciplinarity and citation impact—a novel perspective on citation accumulation," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    9. Chen, Shiji & Qiu, Junping & Arsenault, Clément & Larivière, Vincent, 2021. "Exploring the interdisciplinarity patterns of highly cited papers," Journal of Informetrics, Elsevier, vol. 15(1).
    10. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    11. Yan, Erjia & Ding, Ying & Cronin, Blaise & Leydesdorff, Loet, 2013. "A bird's-eye view of scientific trading: Dependency relations among fields of science," Journal of Informetrics, Elsevier, vol. 7(2), pages 249-264.
    12. Bornmann, Lutz & Ganser, Christian & Tekles, Alexander, 2022. "Simulation of the h index use at university departments within the bibliometrics-based heuristics framework: Can the indicator be used to compare individual researchers?," Journal of Informetrics, Elsevier, vol. 16(1).
    13. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.
    14. Whalen, Ryan, 2018. "Boundary spanning innovation and the patent system: Interdisciplinary challenges for a specialized examination system," Research Policy, Elsevier, vol. 47(7), pages 1334-1343.
    15. Keisuke Okamura, 2019. "Interdisciplinarity revisited: evidence for research impact and dynamism," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    16. Jingjing Ren & Fang Wang & Minglu Li, 2023. "Dynamics and characteristics of interdisciplinary research in scientific breakthroughs: case studies of Nobel-winning research in the past 120 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4383-4419, August.
    17. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    18. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2017. "Do interdisciplinary research teams deliver higher gains to science?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 317-336, April.
    19. Chen, Dar-zen & Huang, Mu-hsuan & Ye, Fred Y., 2013. "A probe into dynamic measures for h-core and h-tail," Journal of Informetrics, Elsevier, vol. 7(1), pages 129-137.
    20. Marcel Clermont & Johanna Krolak & Dirk Tunger, 2021. "Does the citation period have any effect on the informative value of selected citation indicators in research evaluations?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1019-1047, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:108:y:2016:i:1:d:10.1007_s11192-016-1958-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.