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  • × author_ss:"Egghe, L."
  1. Egghe, L.; Guns, R.; Rousseau, R.; Leuven, K.U.: Erratum (2012) 0.02
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    Date
    14. 2.2012 12:53:22
    Language
    e
  2. Egghe, L.: Empirical and combinatorial study of country occurrences in multi-authored papers (2006) 0.02
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    Abstract
    Papers written by several authors can be classified according to the countries of the author affiliations. The empirical part of this paper consists of two datasets. One dataset consists of 1,035 papers retrieved via the search "pedagog*" in the years 2004 and 2005 (up to October) in Academic Search Elite which is a case where phi(m) = the number of papers with m =1, 2,3 ... authors is decreasing, hence most of the papers have a low number of authors. Here we find that #, m = the number of times a country occurs j times in a m-authored paper, j =1, ..., m-1 is decreasing and that # m, m is much higher than all the other #j, m values. The other dataset consists of 3,271 papers retrieved via the search "enzyme" in the year 2005 (up to October) in the same database which is a case of a non-decreasing phi(m): most papers have 3 or 4 authors and we even find many papers with a much higher number of authors. In this case we show again that # m, m is much higher than the other #j, m values but that #j, m is not decreasing anymore in j =1, ..., m-1, although #1, m is (apart from # m, m) the largest number amongst the #j,m. The combinatorial part gives a proof of the fact that #j,m decreases for j = 1, m-1, supposing that all cases are equally possible. This shows that the first dataset is more conform with this model than the second dataset. Explanations for these findings are given. From the data we also find the (we think: new) distribution of number of papers with n =1, 2,3,... countries (i.e. where there are n different countries involved amongst the m (a n) authors of a paper): a fast decreasing function e.g. as a power law with a very large Lotka exponent.
    Language
    e
  3. Egghe, L.: Relations between the continuous and the discrete Lotka power function (2005) 0.02
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    Abstract
    The discrete Lotka power function describes the number of sources (e.g., authors) with n = 1, 2, 3, ... items (e.g., publications). As in econometrics, informetrics theory requires functions of a continuous variable j, replacing the discrete variable n. Now j represents item densities instead of number of items. The continuous Lotka power function describes the density of sources with item density j. The discrete Lotka function one obtains from data, obtained empirically; the continuous Lotka function is the one needed when one wants to apply Lotkaian informetrics, i.e., to determine properties that can be derived from the (continuous) model. It is, hence, important to know the relations between the two models. We show that the exponents of the discrete Lotka function (if not too high, i.e., within limits encountered in practice) and of the continuous Lotka function are approximately the same. This is important to know in applying theoretical results (from the continuous model), derived from practical data.
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  4. Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996) 0.01
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    Language
    e
    Source
    Journal of information science. 22(1996) no.3, S.165-170
  5. Egghe, L.: ¬A universal method of information retrieval evaluation : the "missing" link M and the universal IR surface (2004) 0.01
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    Date
    14. 8.2004 19:17:22
    Language
    e
  6. Egghe, L.: Influence of adding or deleting items and sources on the h-index (2010) 0.01
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    Abstract
    Adding or deleting items such as self-citations has an influence on the h-index of an author. This influence will be proved mathematically in this article. We hereby prove the experimental finding in E. Gianoli and M.A. Molina-Montenegro ([2009]) that the influence of adding or deleting self-citations on the h-index is greater for low values of the h-index. Why this is logical also is shown by a simple theoretical example. Adding or deleting sources such as adding or deleting minor contributions of an author also has an influence on the h-index of this author; this influence is modeled in this article. This model explains some practical examples found in X. Hu, R. Rousseau, and J. Chen (in press).
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  7. Egghe, L.: Little science, big science and beyond (1994) 0.00
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  8. Egghe, L.: Expansion of the field of informetrics : the second special issue (2006) 0.00
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  9. Egghe, L.: Expansion of the field of informetrics : origins and consequences (2005) 0.00
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  10. Egghe, L.: Special features of the author - publication relationship and a new explanation of Lotka's law based on convolution theory (1994) 0.00
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  11. Egghe, L.: Note on a possible decomposition of the h-Index (2013) 0.00
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  12. Egghe, L.: ¬The Hirsch index and related impact measures (2010) 0.00
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  13. Egghe, L.: ¬A noninformetric analysis of the relationship between citation age and journal productivity (2001) 0.00
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    Abstract
    A problem, raised by Wallace (JASIS, 37,136-145,1986), on the relation between the journal's median citation age and its number of articles is studied. Leaving open the problem as such, we give a statistical explanation of this relationship, when replacing "median" by "mean" in Wallace's problem. The cloud of points, found by Wallace, is explained in this sense that the points are scattered over the area in first quadrant, limited by a curve of the form y=1 + E/x**2 where E is a constant. This curve is obtained by using the Central Limit Theorem in statistics and, hence, has no intrinsic informetric foundation. The article closes with some reflections on explanations of regularities in informetrics, based on statistical, probabilistic or informetric results, or on a combination thereof
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  14. Egghe, L.: ¬A good normalized impact and concentration measure (2014) 0.00
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  15. Rousseau, R.; Egghe, L.; Guns, R.: Becoming metric-wise : a bibliometric guide for researchers (2018) 0.00
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    Classification
    AZC (E)
    GHBS
    AZC (E)
    Language
    e
  16. Egghe, L.; Ravichandra Rao, I.K.: Duality revisited : construction of fractional frequency distributions based on two dual Lotka laws (2002) 0.00
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    Abstract
    Fractional frequency distributions of, for example, authors with a certain (fractional) number of papers are very irregular and, therefore, not easy to model or to explain. This article gives a first attempt to this by assuming two simple Lotka laws (with exponent 2): one for the number of authors with n papers (total count here) and one for the number of papers with n authors, n E N. Based an an earlier made convolution model of Egghe, interpreted and reworked now for discrete scores, we are able to produce theoretical fractional frequency distributions with only one parameter, which are in very close agreement with the practical ones as found in a large dataset produced earlier by Rao. The article also shows that (irregular) fractional frequency distributions are a consequence of Lotka's law, and are not examples of breakdowns of this famous historical law.
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  17. Egghe, L.: ¬The amount of actions needed for shelving and reshelving (1996) 0.00
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  18. Egghe, L.; Rousseau, R.: Duality in information retrieval and the hypegeometric distribution (1997) 0.00
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