The i100-index, i1000-index and i10,000-index: expansion and fortification of the Google Scholar h-index for finer-scale citation descriptions and researcher classification

Abstract

The Hirsch or h-index continues to be one of the most popular author-based metrics, despite some of its flaws and limitations. In some cases, citations to some academics’ work are increasing at a phenomenal pace, and in some exceptional cases such as Highly Cited Researchers (HCRs), whether alive or deceased, citation counts to their work have reached tens or hundreds of thousands, with h-indexes in the hundreds. Although the h-index currently has one additional derivative index, the i10-index, which is a measure of the number of publications with 10 or more citations, the i10-index is clearly not a sufficient differentiating factor for academics with very high citation counts such as HCRs. In this letter, an expansion of this metric is proposed to include an i100-index, an i1000-index, and an i10,000-index, which indicate the number of publications with 100, 1000, or 10,000 or more citations, respectively. These three new, expanded and/or modified metrics that are based on the h-index may assist in more effectively differentiating the top echelon of HCRs or leaders in a specific field of study. The i100-, i1000-, and i10,000-indexes for 10 HCRs (Michel Foucault, Ronald C. Kessler, Graham Colditz, Sigmund Freud, JoAnn E. Manson, Shizuo Akira, Pierre Bourdieu, Robert Langer, Eric Lander, and Bert Vogelstein) were calculated. Limitations to these three new proposed h-index-based indexes are noted.

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Notes

  1. 1.

    https://clarivate.com/news/global-highly-cited-researchers-2019-list-reveals-top-talent-in-the-sciences-and-social-sciences/; https://recognition.webofsciencegroup.com/awards/highly-cited/2019/ (November 19, 2019; last accessed: December 1, 2020).

  2. 2.

    http://www.webometrics.info/en/hlargerthan100 (April, 2020; last accessed; September 26, 2020).

References

  1. Bornmann, L., & Leydesdorff, L. (2018). Count highly-cited papers instead of papers with h citations: Use normalized citation counts and compare “like with like”! Scientometrics, 115(2), 1119–1123. https://doi.org/10.1007/s11192-018-2682-1.

    Article  Google Scholar 

  2. Brembs, B., Button, K., & Munafò, M. (2013). Deep impact: Unintended consequences of journal rank. Frontiers in Human Neuroscience, 7, 291. https://doi.org/10.3389/fnhum.2013.00291.

    Article  Google Scholar 

  3. Dinsmore, A., Allen, L., & Dolby, K. (2014). Alternative perspectives on impact: The potential of ALMs and altmetrics to inform funders about research impact. PLoS Biology, 12(11), e1002003. https://doi.org/10.1371/journal.pbio.1002003.

    Article  Google Scholar 

  4. Dobránszki, J., & Teixeira da Silva, J. A. (2019). Corrective factors for author- and journal-based metrics impacted by citations to accommodate for retractions. Scientometrics, 121(1), 387–398. https://doi.org/10.1007/s11192-019-03190-0.

    Article  Google Scholar 

  5. Eom, Y.-H., & Fortunato, S. (2011). Characterizing and modeling citation dynamics. PLoS ONE, 6(9), e24926. https://doi.org/10.1371/journal.pone.0024926.

    Article  Google Scholar 

  6. Hirsch, J. E. (2019). hα: An index to quantify an individual’s scientific leadership. Scientometrics, 118(2), 673–686. https://doi.org/10.1007/s11192-018-2994-1.

    Article  Google Scholar 

  7. Hu, G.-Y., Wang, L., Ni, R., & Liu, W.-S. (2020). Which h-index? An exploration within the Web of Science. Scientometrics, 123(3), 1225–1233. https://doi.org/10.1007/s11192-020-03425-5.

    Article  Google Scholar 

  8. Ioannidis, J. P. A., Baas, J., Klavans, R., & Boyack, K. W. (2019). A standardized citation metrics author database annotated for scientific field. PLoS Biology, 17(8), e3000384. https://doi.org/10.1371/journal.pbio.3000384.

    Article  Google Scholar 

  9. Ioannidis, J. P. A., Klavans, R., & Boyack, K. W. (2018). Thousands of scientists publish a paper every five days. Nature, 561, 167–169. https://doi.org/10.1038/d41586-018-06185-8.

    Article  Google Scholar 

  10. Jensenius, F., Htun, M., Samuels, D., Singer, D., Lawrence, A., & Chwe, M. (2018). The benefits and pitfalls of Google Scholar. PS: Political Science & Politics, 51(4), 820–824. https://doi.org/10.1017/S104909651800094X.

    Article  Google Scholar 

  11. Kalcioglu, M. T., Ileri, Y., Ozdamar, O. I., Yilmaz, U., & Tekin, M. (2018). Evaluation of the academic productivity of the top 100 worldwide physicians in the field of otorhinolaryngology and head and neck surgery using the Google Scholar h-index as the bibliometrics ranking system. The Journal of Laryngology & Otology, 132(12), 1097–1101. https://doi.org/10.1017/s0022215118002190.

    Article  Google Scholar 

  12. McCoy, A. B., Sittig, D. F., Lin, J., & Wright, A. (2019). Identification and ranking of biomedical informatics researcher citation statistics through a Google Scholar scraper. In AMIA Annual Symposium Proceedings, 2019 (pp 655–663). PMCID: PMC7153158

  13. Montazerian, M., Zanotto, E. D., & Eckert, H. (2019). A new parameter for (normalized) evaluation of H-index: Countries as a case study. Scientometrics, 118(3), 1065–1078. https://doi.org/10.1007/s11192-018-2996-z.

    Article  Google Scholar 

  14. Nieminen, P., Carpenter, J., Rucker, G., & Schumacher, M. (2006). The relationship between quality of research and citation frequency. BMC Medical Research Methodology, 6, 42. https://doi.org/10.1186/1471-2288-6-42.

    Article  Google Scholar 

  15. O’Kelly, F., Fernandez, N., & Koyle, M. A. (2019). Predatory publishing or a lack of peer review transparency? A contemporary analysis of indexed open and non-open access articles in paediatric urology. Journal of Pediatric Urology, 15(2), 159.e1–159.e7. https://doi.org/10.1016/j.jpurol.2018.08.019.

  16. Roldan-Valadez, E., Salazar-Ruiz, S. Y., Ibarra-Contreras, R., & Rios, C. (2019). Current concepts on bibliometrics: a brief review about impact factor, Eigenfactor score, CiteScore, SCImago Journal Rank, Source-Normalised Impact per Paper, H-index, and alternative metrics. Irish Journal of Medical Science, 188(3), 939–951. https://doi.org/10.1007/s11845-018-1936-5.

    Article  Google Scholar 

  17. Rousseau, R., & Leuven, K. U. (2008). Reflections on recent developments of the h-index and h-type indices. COLLNET Journal of Scientometrics and Information Management, 2(1), 1–8. https://doi.org/10.1080/09737766.2008.10700835.

    Article  Google Scholar 

  18. Schmoch, U. (2020). Mean values of skewed distributions in the bibliometric assessment of research units. Scientometrics. https://doi.org/10.1007/s11192-020-03476-8.

    Article  Google Scholar 

  19. Teixeira da Silva, J. A. (2018). The Google Scholar h-index: Useful but burdensome metric. Scientometrics, 117(1), 631–635. https://doi.org/10.1007/s11192-018-2859-7.

    Article  Google Scholar 

  20. Teixeira da Silva, J. A., & Bernès, S. (2018). Clarivate Analytics: Continued omnia vanitas impact factor culture. Science and Engineering Ethics, 24(1), 291–297. https://doi.org/10.1007/s11948-017-9873-7.

    Article  Google Scholar 

  21. Teixeira da Silva, J. A., & Dobránszki, J. (2018a). Multiple versions of the h-index: Cautionary use for formal academic purposes. Scientometrics, 115(2), 1107–1113. https://doi.org/10.1007/s11192-018-2680-3.

    Article  Google Scholar 

  22. Teixeira da Silva, J. A., & Dobránszki, J. (2018b). Rejoinder to “Multiple versions of the h-index: Cautionary use for formal academic purposes”. Scientometrics, 115(2), 1131–1137. https://doi.org/10.1007/s11192-018-2684-z.

    Article  Google Scholar 

  23. Thoma, B., & Chan, T. M. (2019). Using Google Scholar to track the scholarly output of research groups. Perspectives on Medical Education, 8(3), 201–205. https://doi.org/10.1007/s40037-019-0515-4.

    Article  Google Scholar 

  24. Yasin, A., Fatima, R., Wen, L., Afzal, W., Azhar, M., & Torkar, R. (2020). On using grey literature and Google Scholar in systematic literature reviews in software engineering. IEEE Access, 8, 36226–36243. https://doi.org/10.1109/ACCESS.2020.2971712.

    Article  Google Scholar 

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Correspondence to Jaime A. Teixeira da Silva.

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Teixeira da Silva, J.A. The i100-index, i1000-index and i10,000-index: expansion and fortification of the Google Scholar h-index for finer-scale citation descriptions and researcher classification. Scientometrics (2021). https://doi.org/10.1007/s11192-020-03831-9

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Keywords

  • Author-based metrics
  • Citations
  • Highly cited researchers
  • i10-index
  • Google scholar
  • Ranking