-
Zornic, N.; Markovic, A.; Jeremic, V.: How the top 500 ARWU can provide a misleading rank (2014)
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-
Vogler, E.; Schindler, C.; Botte, A.; Rittberger, M.: Are altmetrics effective in transdisciplinary research fields? : altmetric coverage of outputs in educational research (2017)
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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
-
Haustein, S.; Sugimoto, C.; Larivière, V.: Social media in scholarly communication : Guest editorial (2015)
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- Date
- 20. 1.2015 18:30:22
-
Ye, F.Y.; Leydesdorff, L.: ¬The "academic trace" of the performance matrix : a mathematical synthesis of the h-index and the integrated impact indicator (I3) (2014)
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- Abstract
- The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.
-
Vinkler, P.: Application of the distribution of citations among publications in scientometric evaluations (2011)
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- Abstract
- The ?-indicator (or ?v-indicator) of a set of journal papers is equal to a hundredth of the total number of citations obtained by the elite set of publications. The number of publications in the elite set P(?) is calculated as the square root of total papers. For greater sets the following equation is used: P(?v) = (10 log P) - 10, where P is the total number of publications. For sets comprising a single or several extreme frequently cited paper, the ?-index may be distorted. Therefore, a new indicator based on the distribution of citations is suggested. Accordingly, the publications are classified into citation categories, of which lower limits are given as 0, and (2n + 1), whereas the upper limits as 2n (n = 0, 2, 3, etc.). The citations distribution score (CDS) index is defined as the sum of weighted numbers of publications in the individual categories. The CDS-index increases logarithmically with the increasing number of citations. The citation distribution rate indicator is introduced by relating the actual CDS-index to the possible maximum. Several size-dependent and size-independent indicators were calculated. It has been concluded that relevant, already accepted scientometric indicators may validate novel indices through resulting in similar conclusions ("converging validation of indicators").
-
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
-
Larivière, V.; Gingras, Y.: ¬The impact factor's Matthew Effect : a natural experiment in bibliometrics (2010)
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-
Larivière, V.; Sugimoto, C.R.; Bergeron, P.: In their own image? : a comparison of doctoral students' and faculty members' referencing behavior (2013)
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Lachance, C.; Poirier, S.; Larivière, V.: ¬The kiss of death? : the effect of being cited in a review on subsequent citations (2014)
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-
Pislyakov, V.; Shukshina, E.: Measuring excellence in Russia : highly cited papers, leading institutions, patterns of national and international collaboration (2014)
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-
Larivière, V.; Gingras, Y.; Sugimoto, C.R.; Tsou, A.: Team size matters : collaboration and scientific impact since 1900 (2015)
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-
Bertin, M.; Atanassova, I.; Gingras, Y.; Larivière, V.: ¬The invariant distribution of references in scientific articles (2016)
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Haustein, S.; Bowman, T.D.; Holmberg, K.; Tsou, A.; Sugimoto, C.R.; Larivière, V.: Tweets as impact indicators : Examining the implications of automated "bot" accounts on Twitter (2016)
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Sugimoto, C.R.; Work, S.; Larivière, V.; Haustein, S.: Scholarly use of social media and altmetrics : A review of the literature (2017)
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Shu, F.; Julien, C.-A.; Larivière, V.: Does the Web of Science accurately represent chinese scientific performance? (2019)
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Larivière, V.; Sugimoto, C.R.; Cronin, B.: ¬A bibliometric chronicling of library and information science's first hundred years (2012)
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Kirchik, O.; Gingras, Y.; Larivière, V.: Changes in publication languages and citation practices and their effect on the scientific impact of Russian science (1993-2010) (2012)
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Lozano, G.A.; Larivière, V.; Gingras, Y.: ¬The weakening relationship between the impact factor and papers' citations in the digital age (2012)
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Larivière, V.; Lozano, G.A.; Gingras, Y.: Are elite journals declining? (2014)
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Haustein, S.; Peters, I.; Sugimoto, C.R.; Thelwall, M.; Larivière, V.: Tweeting biomedicine : an analysis of tweets and citations in the biomedical literature (2014)
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