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Diodato, V.: Dictionary of bibliometrics (1994)
0.14
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- Footnote
- Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
-
Rostaing, H.; Barts, N.; Léveillé, V.: Bibliometrics: representation instrument of the multidisciplinary positioning of a scientific area : Implementation for an Advisory Scientific Committee (2007)
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- Date
- 30.12.2007 11:22:39
-
Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009)
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- Date
- 22. 3.2009 19:22:35
-
Boyce, B.R.; Meadow, C.T.; Kraft, D.H.: Measurement in information science (1994)
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- Footnote
- Rez in: JASIS 47(1996) no.3, S.257-258 (V. Raghavan)
-
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
-
Cano, V.: Bibliometric overview of library and information science research in Spain (1999)
0.03
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-
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)
0.03
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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.
-
Nicholls, P.T.: Empirical validation of Lotka's law (1986)
0.03
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- Source
- Information processing and management. 22(1986), S.417-419
-
Nicolaisen, J.: Citation analysis (2007)
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- Date
- 13. 7.2008 19:53:22
-
Fiala, J.: Information flood : fiction and reality (1987)
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- Source
- Thermochimica acta. 110(1987), S.11-22
-
Ahlgren, P.; Järvelin, K.: Measuring impact of twelve information scientists using the DCI index (2010)
0.03
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- Abstract
- The Discounted Cumulated Impact (DCI) index has recently been proposed for research evaluation. In the present work an earlier dataset by Cronin and Meho (2007) is reanalyzed, with the aim of exemplifying the salient features of the DCI index. We apply the index on, and compare our results to, the outcomes of the Cronin-Meho (2007) study. Both authors and their top publications are used as units of analysis, which suggests that, by adjusting the parameters of evaluation according to the needs of research evaluation, the DCI index delivers data on an author's (or publication's) lifetime impact or current impact at the time of evaluation on an author's (or publication's) capability of inviting citations from highly cited later publications as an indication of impact, and on the relative impact across a set of authors (or publications) over their lifetime or currently.
-
Danell, R.: Can the quality of scientific work be predicted using information on the author's track record? (2011)
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- Abstract
- Many countries are moving towards research policies that emphasize excellence; consequently; they develop evaluation systems to identify universities, research groups, and researchers that can be said to be "excellent." Such active research policy strategies, in which evaluations are used to concentrate resources, are based on an unsubstantiated assumption that researchers' track records are indicative of their future research performance. In this study, information on authors' track records (previous publication volume and previous citation rate) is used to predict the impact of their articles. The study concludes that, to a certain degree, the impact of scientific work can be predicted using information on how often an author's previous publications have been cited. The relationship between past performance and the citation rate of articles is strongest at the high end of the citation distribution. The implications of these results are discussed in the context of a cumulative advantage process.
-
Pernik, V.; Schlögl, C.: Möglichkeiten und Grenzen von Web Structure Mining am Beispiel von informationswissenschaftlichen Hochschulinstituten im deutschsprachigen Raum (2006)
0.03
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-
Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998)
0.02
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- Date
- 22. 5.1999 19:22:35
-
Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001)
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- Date
- 22. 7.2006 15:22:28
-
Bookstein, A.: Informetric distributions : I. Unified overview (1990)
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- Date
- 22. 7.2006 18:55:29
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Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990)
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- Date
- 22. 7.2006 18:55:55
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Larivière, V.; Archambault, V.; Gingras, Y.; Vignola-Gagné, E.: ¬The place of serials in referencing practices : comparing natural sciences and engineering with social sciences and humanities (2006)
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