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  • × theme_ss:"Informetrie"
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  1. Prathap, G.: Quantity, quality, and consistency as bibliometric indicators (2014) 0.02 
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  2. Prathap, G.: Measures for bibliometric size, impact, and concentration (2015) 0.02 
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  3. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.02 
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    Date
    18. 3.2014 19:13:22
  4. Persson, O.; Melin, G.: Equalization, growth and integration of science (1996) 0.02 
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  5. Prathap, G.: ¬A three-class, three-dimensional bibliometric performance indicator (2014) 0.02 
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  6. Vinkler, P.: Core indicators and professional recognition of scientometricians (2017) 0.02 
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    Abstract
    The publication performance of 30 scientometricians is studied. The individuals are classified into 3 cohorts according to their manifested professional recognition, as Price medalists (Pm), members of the editorial board of Scientometrics and the Journal of Informetrics (Rw), and session chairs (Sc) at an International Society of Scientometrics and Informetrics (ISSI) conference. Several core impact indicators are calculated: h, g, p, citation distribution score (CDS), percentage rank position (PRP), and weight of influence of papers (WIP10). The indices significantly correlate with each other. The mean value of the indices of the cohorts decreases parallel with the decrease in professional recognition: Pm?>?Rw?>?Sc. The 30 scientometricians studied were clustered according to the core impact indices. The members in the clusters so obtained overlap only partly with the members in the cohorts made by professional recognition. The Total Overlap is calculated by dividing the sum of the diagonal elements in the cohorts-clusters matrix with the total number of elements, times 100. The highest overlap (76.6%) was obtained with the g-index. Accordingly, the g-index seems to have the greatest discriminative power in the system studied. The cohorts-clusters method may be used for validating scientometric indicators.
  7. 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) 0.02 
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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.
  8. Hooydonk, G. Van: Journal production and journal impact factor (1996) 0.01 
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  9. Marx, W.; Gramm, G.: Literaturflut - Informationslawine - Wissensexplosion : Wächst der Wissenschaft das Wissen über den Kopf? (1997) 0.01 
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  10. Ohly, H.P.: ¬Der 'Stand der Technik' : eine bibliometrische Betrachtungsweise (2000) 0.01 
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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
  11. 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) 0.01 
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  12. Prathap, G.: ¬A thermodynamic explanation for the Glänzel-Schubert model for the h-index (2011) 0.01 
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  13. Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009) 0.01 
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  14. Prathap, G.: Fractionalized exergy for evaluating research performance (2011) 0.01 
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  15. Prathap, G.: ¬The zynergy-index and the formula for the h-index (2014) 0.01 
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  16. Haley, M.R.; McGee, M.K.: ¬A parametric "parent metric" approach for comparing maximum-normalized journal ranking metrics (2018) 0.01 
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    Abstract
    This article proposes a parametric approach for facilitating inter-metric and inter-field comparisons of citation-based journal ranking metrics. The mechanism is simple to apply and adjusts for metric magnitude differentials and distributional asymmetries in the rank-score curves. The method is demonstrated using h-index, AWCR-index, g-index, and e-index data from journals in Accounting, Economics, and Finance.
  17. Reichmann, G.; Schlögl, C.: Möglichkeiten zur Steuerung der Ergebnisse einer Forschungsevaluation (2021) 0.01 
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  18. Raan, A.F.J. van: Statistical properties of bibliometric indicators : research group indicator distributions and correlations (2006) 0.01 
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    Date
    22. 7.2006 16:20:22
  19. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.01 
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    Date
    22. 3.2009 19:22:35
  20. Egghe, L.: Mathematical study of h-index sequences (2009) 0.01 
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    Abstract
    This paper studies mathematical properties of h-index sequences as developed by Liang [Liang, L. (2006). h-Index sequence and h-index matrix: Constructions and applications. Scientometrics, 69(1), 153-159]. For practical reasons, Liming studies such sequences where the time goes backwards while it is more logical to use the time going forward (real career periods). Both type of h-index sequences are studied here and their interrelations are revealed. We show cases where these sequences are convex, linear and concave. We also show that, when one of the sequences is convex then the other one is concave, showing that the reverse-time sequence, in general, cannot be used to derive similar properties of the (difficult to obtain) forward time sequence. We show that both sequences are the same if and only if the author produces the same number of papers per year. If the author produces an increasing number of papers per year, then Liang's h-sequences are above the "normal" ones. All these results are also valid for g- and R-sequences. The results are confirmed by the h-, g- and R-sequences (forward and reverse time) of the author.

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