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  • × author_ss:"Egghe, L."
  • × author_ss:"Guns, R."
  • × year_i:[2010 TO 2020}
  1. Egghe, L.; Guns, R.; Rousseau, R.; Leuven, K.U.: Erratum (2012) 0.03
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    Date
    14. 2.2012 12:53:22
    Type
    a
  2. Egghe, L.; Guns, R.; Rousseau, R.: Thoughts on uncitedness : Nobel laureates and Fields medalists as case studies (2011) 0.00
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    Abstract
    Contrary to what one might expect, Nobel laureates and Fields medalists have a rather large fraction (10% or more) of uncited publications. This is the case for (in total) 75 examined researchers from the fields of mathematics (Fields medalists), physics, chemistry, and physiology or medicine (Nobel laureates). We study several indicators for these researchers, including the h-index, total number of publications, average number of citations per publication, the number (and fraction) of uncited publications, and their interrelations. The most remarkable result is a positive correlation between the h-index and the number of uncited articles. We also present a Lotkaian model, which partially explains the empirically found regularities.
    Type
    a
  3. Egghe, L.; Guns, R.: Applications of the generalized law of Benford to informetric data (2012) 0.00
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    Abstract
    In a previous work (Egghe, 2011), the first author showed that Benford's law (describing the logarithmic distribution of the numbers 1, 2, ... , 9 as first digits of data in decimal form) is related to the classical law of Zipf with exponent 1. The work of Campanario and Coslado (2011), however, shows that Benford's law does not always fit practical data in a statistical sense. In this article, we use a generalization of Benford's law related to the general law of Zipf with exponent ? > 0. Using data from Campanario and Coslado, we apply nonlinear least squares to determine the optimal ? and show that this generalized law of Benford fits the data better than the classical law of Benford.
    Type
    a
  4. Rousseau, R.; Egghe, L.; Guns, R.: Becoming metric-wise : a bibliometric guide for researchers (2018) 0.00
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    Abstract
    Aims to inform researchers about metrics so that they become aware of the evaluative techniques being applied to their scientific output. Understanding these concepts will help them during their funding initiatives, and in hiring and tenure. The book not only describes what indicators do (or are designed to do, which is not always the same thing), but also gives precise mathematical formulae so that indicators can be properly understood and evaluated. Metrics have become a critical issue in science, with widespread international discussion taking place on the subject across scientific journals and organizations. As researchers should know the publication-citation context, the mathematical formulae of indicators being used by evaluating committees and their consequences, and how such indicators might be misused, this book provides an ideal tome on the topic. Provides researchers with a detailed understanding of bibliometric indicators and their applications. Empowers researchers looking to understand the indicators relevant to their work and careers. Presents an informed and rounded picture of bibliometrics, including the strengths and shortcomings of particular indicators. Supplies the mathematics behind bibliometric indicators so they can be properly understood. Written by authors with longstanding expertise who are considered global leaders in the field of bibliometrics