-
Rousseau, R.: ¬A table for estimating the exponent in Lotka's law (1993)
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-
Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998)
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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
-
Diodato, V.: Dictionary of bibliometrics (1994)
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- Footnote
- Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
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Bookstein, A.: Informetric distributions : I. Unified overview (1990)
0.02
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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
-
Persson, O.; Melin, G.: Equalization, growth and integration of science (1996)
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- Abstract
- Presents a study of the production of scientific papers, coauthorships and R&D expenditures in the OECD countries. Discusses the distribution of papers in the journal 'Science' by OECD country in comparison with 'Science Citation Index' papers as a whole and compares these to the distribution of R&D investments
-
White, H.D.: Author cocitation analysis and pearson's r (2003)
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- Abstract
- In their article "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient," Ahlgren, Jarneving, and Rousseau fault traditional author cocitation analysis (ACA) for using Pearson's r as a measure of similarity between authors because it fails two tests of stability of measurement. The instabilities arise when rs are recalculated after a first coherent group of authors has been augmented by a second coherent group with whom the first has little or no cocitation. However, AJ&R neither cluster nor map their data to demonstrate how fluctuations in rs will mislead the analyst, and the problem they pose is remote from both theory and practice in traditional ACA. By entering their own rs into multidimensional scaling and clustering routines, I show that, despite r's fluctuations, clusters based an it are much the same for the combined groups as for the separate groups. The combined groups when mapped appear as polarized clumps of points in two-dimensional space, confirming that differences between the groups have become much more important than differences within the groups-an accurate portrayal of what has happened to the data. Moreover, r produces clusters and maps very like those based an other coefficients that AJ&R mention as possible replacements, such as a cosine similarity measure or a chi square dissimilarity measure. Thus, r performs well enough for the purposes of ACA. Accordingly, I argue that qualitative information revealing why authors are cocited is more important than the cautions proposed in the AJ&R critique. I include notes an topics such as handling the diagonal in author cocitation matrices, lognormalizing data, and testing r for significance.
-
Rousseau, S.; Rousseau, R.: Metric-wiseness (2015)
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-
Liang, L.: R-Sequences : relative indicators for the rhythm of science (2005)
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- Abstract
- Like most activities in the world, scientific evolution has its own rhythm. How can this evolutionary rhythm be described and made visible? Do different fields have different rhythms, and how can they be measured? In order to answer these questions a relative indicator, called R-sequence, was designed. This indicator is time dependent, derived from publication and citation data, but independent of the absolute number of publications, as weIl as the absolute number of citations, and can therefore be used in a comparison of different scientific fields, nations, Institutes, or journals. Two caiculation methods of the R-sequence-the triangle method and the parallelogram method-are introduced. As a case study JASIS(T)'s R-sequence has been obtained.
-
Egghe, L.; Liang, L.; Rousseau, R.: Fundamental properties of rhythm sequences (2008)
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- Abstract
- Fundamental mathematical properties of rhythm sequences are studied. In particular, a set of three axioms for valid rhythm indicators is proposed, and it is shown that the R-indicator satisfies only two out of three but that the R-indicator satisfies all three. This fills a critical, logical gap in the study of these indicator sequences. Matrices leading to a constant R-sequence are called baseline matrices. They are characterized as matrices with constant w-year diachronous impact factors. The relation with classical impact factors is clarified. Using regression analysis matrices with a rhythm sequence that is on average equal to 1 (smaller than 1, larger than 1) are characterized.
-
Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005)
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- Date
- 20. 1.2007 17:02:22
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
-
Henzler, R.: Bibliometrische Methoden der Termanalyse (1980)
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-
Vasiljev, A.: ¬The law of requisite variety as applied to subject indexing and retrieval (1989)
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- Source
- Klassifikation und Ordnung. Tagungsband 12. Jahrestagung der Gesellschaft für Klassifikation, Darmstadt 17.-19.3.1988. Hrsg.: R. Wille
-
Harries, G.; Wilkinson, D.; Price, L.; Fairclough, R.; Thelwall, M.: Hyperlinks as a data source for science mapping : making sense of it all (2005)
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-
Rousseau, R.: Egghe's g-index is not a proper concentration measure (2015)
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-
Bornmann, L.; Bauer, J.; Haunschild, R.: Distribution of women and men among highly cited scientists (2015)
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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)
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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.
- Object
- R-Index
-
Schramm, R.; Bartkowski, A.: Patentindikatoren zur Ermittlung von Kerninformationen (1996)
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