-
Ding, Y.: Applying weighted PageRank to author citation networks (2011)
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- Date
- 22. 1.2011 13:02:21
-
Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014)
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- Abstract
- This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
-
Chang, Y.-W.; Huang, M.-H.: ¬A study of the evolution of interdisciplinarity in library and information science : using three bibliometric methods (2012)
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- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.22-33
-
Bu, Y.; Ding, Y.; Xu, J.; Liang, X.; Gao, G.; Zhao, Y.: Understanding success through the diversity of collaborators and the milestone of career (2018)
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Zhang, C.; Bu, Y.; Ding, Y.; Xu, J.: Understanding scientific collaboration : homophily, transitivity, and preferential attachment (2018)
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-
Zhai, Y; Ding, Y.; Wang, F.: Measuring the diffusion of an innovation : a citation analysis (2018)
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-
Yan, E.; Ding, Y.: Weighted citation : an indicator of an article's prestige (2010)
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-
Liu, Y.; Rousseau, R.: Citation analysis and the development of science : a case study using articles by some Nobel prize winners (2014)
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-
Yan, E.; Ding, Y.: Discovering author impact : a PageRank perspective (2011)
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Zhang, C.; Liu, X.; Xu, Y.(C.); Wang, Y.: Quality-structure index : a new metric to measure scientific journal influence (2011)
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-
Onodera, N.; Iwasawa, M.; Midorikawa, N.; Yoshikane, F.; Amano, K.; Ootani, Y.; Kodama, T.; Kiyama, Y.; Tsunoda, H.; Yamazaki, S.: ¬A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search (2011)
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-
Tsay, M.-y.; Shu, Z.-y.: Journal bibliometric analysis : a case study on the Journal of Documentation (2011)
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-
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.
-
Bu, Y.; Ding, Y.; Liang, X.; Murray, D.S.: Understanding persistent scientific collaboration (2018)
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-
Min, C.; Ding, Y.; Li, J.; Bu, Y.; Pei, L.; Sun, J.: Innovation or imitation : the diffusion of citations (2018)
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-
Liu, Y.; Rousseau, R.: Towards a representation of diffusion and interaction of scientific ideas : the case of fiber optics communication (2012)
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-
Fassin, Y.: ¬A new qualitative rating system for scientific publications and a fame index for academics (2018)
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-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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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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-
Shibata, N.; Kajikawa, Y.; Sakata, I.: Link prediction in citation networks (2012)
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