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  1. Schreiber, M.: Revisiting the g-index : the average number of citations in the g-core (2009) 0.14
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    Abstract
    The g-index is discussed in terms of the average number of citations of the publications in the g-core, showing that it combines features of the h-index and the A-index in one number. For a visualization, data of 8 famous physicists are presented and analyzed. In comparison with the h-index, the g-index increases between 67% and 144%, on average by a factor of 2.
    Object
    g-index
  2. Schreiber, M.: Do we need the g-index? (2013) 0.13
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    Abstract
    Using a very small sample of 8 data sets it was recently shown by De Visscher (2011) that the g-index is very close to the square root of the total number of citations. It was argued that there is no bibliometrically meaningful difference. Using another somewhat larger empirical sample of 26 data sets I show that the difference may be larger and I argue in favor of the g-index.
    Object
    g-index
  3. Schreiber, M.: Fractionalized counting of publications for the g-Index (2009) 0.12
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    Abstract
    L. Egghe ([2008]) studied the h-index (Hirsch index) and the g-index, counting the authorship of cited articles in a fractional way. But his definition of the gF-index for the case that the article count is fractionalized yielded values that were close to or even larger than the original g-index. Here I propose an alternative definition by which the g-index is modified in such a way that the resulting gm-index is always smaller than the original g-index. Based on the interpretation of the g-index as the highest number of articles of a scientist that received on average g or more citations, in the specification of the new gm-index the articles are counted fractionally not only for the rank but also for the average.
    Object
    g-index
  4. Schreiber, M.: ¬An empirical investigation of the g-index for 26 physicists in comparison with the h-index, the A-index, and the R-index (2008) 0.09
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    Abstract
    J.E. Hirsch (2005) introduced the h-index to quantify an individual's scientific research output by the largest number h of a scientist's papers that received at least h citations. To take into account the highly skewed frequency distribution of citations, L. Egghe (2006a) proposed the g-index as an improvement of the h-index. I have worked out 26 practical cases of physicists from the Institute of Physics at Chemnitz University of Technology, and compare the h and g values in this study. It is demonstrated that the g-index discriminates better between different citation patterns. This also can be achieved by evaluating B.H. Jin's (2006) A-index, which reflects the average number of citations in the h-core, and interpreting it in conjunction with the h-index. h and A can be combined into the R-index to measure the h-core's citation intensity. I also have determined the A and R values for the 26 datasets. For a better comparison, I utilize interpolated indices. The correlations between the various indices as well as with the total number of papers and the highest citation counts are discussed. The largest Pearson correlation coefficient is found between g and R. Although the correlation between g and h is relatively strong, the arrangement of the datasets is significantly different depending on whether they are put into order according to the values of either h or g.
  5. Bonitz, M.; Scharnhorst, A.: National science systems and the Matthew effect for countries (2000) 0.05
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    Source
    Globalisierung und Wissensorganisation: Neue Aspekte für Wissen, Wissenschaft und Informationssysteme: Proceedings der 6. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation Hamburg, 23.-25.9.1999. Hrsg.: H.P. Ohly, G. Rahmstorf u. A. Sigel
  6. Scholarly metrics under the microscope : from citation analysis to academic auditing (2015) 0.05
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    Date
    22. 1.2017 17:12:50
    Editor
    Cronin, B. u. C.R. Sugimoto
    Type
    m
  7. Harries, G.; Wilkinson, D.; Price, L.; Fairclough, R.; Thelwall, M.: Hyperlinks as a data source for science mapping : making sense of it all (2005) 0.05
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  8. Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005) 0.05
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    Date
    20. 1.2007 17:02:22
  9. Schreiber, M.: Inconsistencies in the highly cited publications indicator (2013) 0.04
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  10. Schreiber, M.: Restricting the h-index to a citation time window : a case study of a timed Hirsch index (2014) 0.04
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  11. ¬The Web of knowledge : Festschrift in honor of Eugene Garfield (2000) 0.04
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    Editor
    Cronin, B. u. H.B. Atkins
    Footnote
    Rez. in: Knowledge organization 28(2001) no.1, S.45-46 (M.J. López Huertas u. E. Jiménez-Contreras); Password 2002, H.3, S.14-19 (W.G. Stock)
    Type
    m
  12. Ye, F.Y.; Yu, S.S.; Leydesdorff, L.: ¬The Triple Helix of university-industry-government relations at the country level and its dynamic evolution under the pressures of globalization (2013) 0.04
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    Abstract
    Using data from the Web of Science (WoS), we analyze the mutual information among university, industry, and government addresses (U-I-G) at the country level for a number of countries. The dynamic evolution of the Triple Helix can thus be compared among developed and developing nations in terms of cross-sectional coauthorship relations. The results show that the Triple Helix interactions among the three subsystems U-I-G become less intensive over time, but unequally for different countries. We suggest that globalization erodes local Triple Helix relations and thus can be expected to have increased differentiation in national systems since the mid-1990s. This effect of globalization is more pronounced in developed countries than in developing ones. In the dynamic analysis, we focus on a more detailed comparison between China and the United States. Specifically, the Chinese Academy of the (Social) Sciences is changing increasingly from a public research institute to an academic one, and this has a measurable effect on China's position in the globalization.
  13. Raan, A.F.J. van: Scaling rules in the science system : influence of field-specific citation characteristics on the impact of research groups (2008) 0.04
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    Date
    22. 3.2009 19:03:12
    Footnote
    Vgl. auch: Costas, R., M. Bordons u. T.N. van Leeuwen u.a.: Scaling rules in the science system: Influence of field-specific citation characteristics on the impact of individual researchers. In: Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.740-753.
  14. Schreiber, M.: ¬A case study of the modified Hirsch index hm accounting for multiple coauthors (2009) 0.04
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  15. Schreiber, M.: ¬A variant of the h-index to measure recent performance (2015) 0.04
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  16. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.04
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    Date
    22. 6.2023 18:07:12
  17. Waltman, L.; Schreiber, M.: On the calculation of percentile-based bibliometric indicators (2013) 0.03
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  18. Diodato, V.: Dictionary of bibliometrics (1994) 0.03
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    Footnote
    Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
    Type
    m
  19. Kurtz, M.J.; Eichhorn, G.; Accomazzi, A.; Grant, C.; Demleitner, M.; Henneken, E.; Murray, S.S.: ¬The effect of use and access on citations (2005) 0.03
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  20. Vogler, E.; Schindler, C.; Botte, A.; Rittberger, M.: Are altmetrics effective in transdisciplinary research fields? : altmetric coverage of outputs in educational research (2017) 0.03
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    Source
    Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras

Types

  • a 370
  • m 20
  • s 6
  • el 4
  • b 1
  • x 1
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