Several scientometric impact indicators [total citations, h, g, and π-index, percentage rank position (PRP), weighted citation share (WCS)] of 190 elite papers of 15 members of the Hungarian Academy of Sciences active in three different fields were calculated. From the indices the PRP indicator proved to be independent of the citation practices in the fields. The PRP index of a journal paper can be calculated in per cent as unity minus (the rank number of the paper by citation frequency within the publishing journal minus one divided with the total number of papers in the journal) times hundred. The sum of the PRP index of the elite papers of a scientist may characterize his or her total publication performance. The size of the elite set of journal papers within the total was calculated by different methods. The h-index and g-index corresponds to the size of the elite, i.e. number of the elite papers according to the h-statistics and g-statistics, respectively. The number of papers in the π-set is equal to the square root of total papers. The π-index equals to one hundredth of citations to the π-set papers. In the present paper the size of the elite set is determined as the number of papers in the h-set, g-set, or π-set, and as 10 % of total papers, or number of papers cited 2, 3, or 5 times the mean citation rate (MCR) of the publishing journal. The π-citation threshold model is presented for demonstrating how MCR and the distribution of citations over the papers may influence the size of the elite set and the corresponding π-index. It was found that the scientific performances concluded from the π-index obtained from elite sets of different size are in good agreement.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Aksnes, D. W. (2003). Characteristics of highly cited papers. Research Evaluation, 12, 159–170.
Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H.-D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5, 346–359.
Bornmann, L., Leydesdorff, L., & Mutz, R. (2013). The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits. Journal of Informetrics, 7, 158–165.
Bornmann, L., & Marx, W. (2014). How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations. Scientometrics, 98, 487–509.
Egghe, L. (2006). Theory and practice of the g-index. Scientometrics, 69, 131–152.
Glänzel, W. (2011). The application of characteristic scores and scales to the evaluation and ranking of scientific journals. Journal of Information Science, 37, 40–48.
Glänzel, W., & Thijs, B. (2012). Using’core documents’ for detecting and labeling new emerging topics. Scientometrics, 91, 399–416.
Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102, 16569–16572.
Iglesias, J. E., & Pecharroman, C. (2007). Scaling the h-index for different scientific ISI fields. Scientometrics, 73, 303–320.
Leydesdorff, L. (2012). Alternatives to the journal impact factor: I3 and top-10 % (or top-25 %?) of the most highly cited papers. Scientometrics, 92, 355–365.
Plomp, R. (1990). The significance of the number of highly cited papers as an indicator of scientific prolificacy. Scientometrics, 19, 185–197.
Schreiber, M. (2010). Twenty Hirsch index variants and other indicators giving more or less preference to highly cited papers. Annalen der Physik (Berlin), 52, 536–554.
Schubert, A., Glänzel, W., & Braun, T. (1989). Scientometric data files. A comprehensive set of indicators on 2649 journals and 96 countries in all major science fields and subfields 1981–1985. Scientometrics, 16, 1–478.
Schreiber, M., Malesios, C. C., & Psarakis, S. (2012). Exploratory factor analysis for the Hirsch index, 17 h-type variants, and some traditional bibliometric indicators. Journal of Informetrics, 6, 347–358.
Vinkler, P. (2003). Relation of relative scientometric indicators. Scientometrics, 58, 687–694.
Vinkler, P. (2007). Eminence of scientists in the light of the h-index and other scientometric indicators. Journal of Information Science, 33, 481–491.
Vinkler, P. (2009). The π-index: A new indicator for assessing scientific impact. Journal of Information Science, 35, 602–612.
Vinkler, P. (2010). The evaluation of research by scientometric indicators (pp. 1–313). Oxford: Chandos Publishing.
Vinkler, P. (2011). Application of the distribution of citations among publications in scientometric evaluations. Journal of the American Society for Information Science and Technology, 62, 1963–1978.
Vinkler, P. (2012). The case of scientometricians with the “absolute relative” impact indicator. Journal of Informetrics, 6, 254–264.
Vinkler, P. (2013). Comparative rank assessment of journal articles. Journal of Informetrics, 7, 712–717.
Vinkler, P. (2014). The use of the percentage rank position index for comparative evaluation of journals. Journal of Informetrics, 8, 340–348.
Wildgaard, L., Schneider, J. W., & Larsen, B. (2014). A review of the characteristics of 108 author-level bibliometric indicators. Scientometrics, 101, 125–158.
About this article
Cite this article
Vinkler, P. The size and impact of the elite set of publications in scientometric assessments. Scientometrics 110, 163–177 (2017). https://doi.org/10.1007/s11192-016-2165-1
- Elite set
- Field dependence
- Percentage rank position