Search (53 results, page 1 of 3)

  • × year_i:[2010 TO 2020}
  • × author_ss:"Bornmann, L."
  1. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.03 
    0.030438973 = product of:
  0.091316916 = sum of:
    0.091316916 = sum of:
      0.020087399 = weight(_text_:of in 1239) [ClassicSimilarity], result of:
        0.020087399 = score(doc=1239,freq=4.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.2932045 = fieldWeight in 1239, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.09375 = fieldNorm(doc=1239)
      0.07122952 = weight(_text_:22 in 1239) [ClassicSimilarity], result of:
        0.07122952 = score(doc=1239,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.46428138 = fieldWeight in 1239, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.09375 = fieldNorm(doc=1239)
  0.33333334 = coord(1/3)
    Date
    18. 3.2014 19:13:22
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.4, S.866-867
  2. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.02 
    0.02129588 = product of:
  0.06388764 = sum of:
    0.06388764 = sum of:
      0.016401293 = weight(_text_:of in 1431) [ClassicSimilarity], result of:
        0.016401293 = score(doc=1431,freq=6.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.23940048 = fieldWeight in 1431, product of:
            2.4494898 = tf(freq=6.0), with freq of:
              6.0 = termFreq=6.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.0625 = fieldNorm(doc=1431)
      0.047486346 = weight(_text_:22 in 1431) [ClassicSimilarity], result of:
        0.047486346 = score(doc=1431,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.30952093 = fieldWeight in 1431, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0625 = fieldNorm(doc=1431)
  0.33333334 = coord(1/3)
    Abstract
    Properties of a percentile-based rating scale needed in bibliometrics are formulated. Based on these properties, P100 was recently introduced as a new citation-rank approach (Bornmann, Leydesdorff, & Wang, 2013). In this paper, we conceptualize P100 and propose an improvement which we call P100'. Advantages and disadvantages of citation-rank indicators are noted.
    Date
    22. 8.2014 17:05:18
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
  3. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.02 
    0.019357719 = product of:
  0.058073156 = sum of:
    0.058073156 = sum of:
      0.022458395 = weight(_text_:of in 4681) [ClassicSimilarity], result of:
        0.022458395 = score(doc=4681,freq=20.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.32781258 = fieldWeight in 4681, product of:
            4.472136 = tf(freq=20.0), with freq of:
              20.0 = termFreq=20.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.046875 = fieldNorm(doc=4681)
      0.03561476 = weight(_text_:22 in 4681) [ClassicSimilarity], result of:
        0.03561476 = score(doc=4681,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.23214069 = fieldWeight in 4681, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=4681)
  0.33333334 = coord(1/3)
    Abstract
    A recent publication in Nature reports that public R&D funding is only weakly correlated with the citation impact of a nation's articles as measured by the field-weighted citation index (FWCI; defined by Scopus). On the basis of the supplementary data, we up-scaled the design using Web of Science data for the decade 2003-2013 and OECD funding data for the corresponding decade assuming a 2-year delay (2001-2011). Using negative binomial regression analysis, we found very small coefficients, but the effects of international collaboration are positive and statistically significant, whereas the effects of government funding are negative, an order of magnitude smaller, and statistically nonsignificant (in two of three analyses). In other words, international collaboration improves the impact of research articles, whereas more government funding tends to have a small adverse effect when comparing OECD countries.
    Date
    8. 1.2019 18:22:45
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.2, S.198-201
  4. Bornmann, L.: How to analyze percentile citation impact data meaningfully in bibliometrics : the statistical analysis of distributions, percentile rank classes, and top-cited papers (2013) 0.02 
    0.018973555 = product of:
  0.056920663 = sum of:
    0.056920663 = sum of:
      0.021305902 = weight(_text_:of in 656) [ClassicSimilarity], result of:
        0.021305902 = score(doc=656,freq=18.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.3109903 = fieldWeight in 656, product of:
            4.2426405 = tf(freq=18.0), with freq of:
              18.0 = termFreq=18.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.046875 = fieldNorm(doc=656)
      0.03561476 = weight(_text_:22 in 656) [ClassicSimilarity], result of:
        0.03561476 = score(doc=656,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.23214069 = fieldWeight in 656, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=656)
  0.33333334 = coord(1/3)
    Abstract
    According to current research in bibliometrics, percentiles (or percentile rank classes) are the most suitable method for normalizing the citation counts of individual publications in terms of the subject area, the document type, and the publication year. Up to now, bibliometric research has concerned itself primarily with the calculation of percentiles. This study suggests how percentiles (and percentile rank classes) can be analyzed meaningfully for an evaluation study. Publication sets from four universities are compared with each other to provide sample data. These suggestions take into account on the one hand the distribution of percentiles over the publications in the sets (universities here) and on the other hand concentrate on the range of publications with the highest citation impact-that is, the range that is usually of most interest in the evaluation of scientific performance.
    Date
    22. 3.2013 19:44:17
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.587-595
  5. Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011) 0.02 
    0.018026924 = product of:
  0.05408077 = sum of:
    0.05408077 = sum of:
      0.024401804 = weight(_text_:of in 4186) [ClassicSimilarity], result of:
        0.024401804 = score(doc=4186,freq=34.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.35617945 = fieldWeight in 4186, product of:
            5.8309517 = tf(freq=34.0), with freq of:
              34.0 = termFreq=34.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4186)
      0.029678967 = weight(_text_:22 in 4186) [ClassicSimilarity], result of:
        0.029678967 = score(doc=4186,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.19345059 = fieldWeight in 4186, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=4186)
  0.33333334 = coord(1/3)
    Abstract
    The Impact Factors (IFs) of the Institute for Scientific Information suffer from a number of drawbacks, among them the statistics-Why should one use the mean and not the median?-and the incomparability among fields of science because of systematic differences in citation behavior among fields. Can these drawbacks be counteracted by fractionally counting citation weights instead of using whole numbers in the numerators? (a) Fractional citation counts are normalized in terms of the citing sources and thus would take into account differences in citation behavior among fields of science. (b) Differences in the resulting distributions can be tested statistically for their significance at different levels of aggregation. (c) Fractional counting can be generalized to any document set including journals or groups of journals, and thus the significance of differences among both small and large sets can be tested. A list of fractionally counted IFs for 2008 is available online at http:www.leydesdorff.net/weighted_if/weighted_if.xls The between-group variance among the 13 fields of science identified in the U.S. Science and Engineering Indicators is no longer statistically significant after this normalization. Although citation behavior differs largely between disciplines, the reflection of these differences in fractionally counted citation distributions can not be used as a reliable instrument for the classification.
    Date
    22. 1.2011 12:51:07
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.217-229
  6. Bornmann, L.; Bauer, J.: Which of the world's institutions employ the most highly cited researchers : an analysis of the data from highlycited.com (2015) 0.00 
    0.0047346456 = product of:
  0.014203936 = sum of:
    0.014203936 = product of:
      0.028407872 = sum of:
        0.028407872 = weight(_text_:of in 1556) [ClassicSimilarity], result of:
          0.028407872 = score(doc=1556,freq=18.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.41465375 = fieldWeight in 1556, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0625 = fieldNorm(doc=1556)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    In 2014, Thomson Reuters published a list of the most highly cited researchers worldwide (highlycited.com). Because the data are freely available for downloading and include the names of the researchers' institutions, we produced a ranking of the institutions on the basis of the number of highly cited researchers per institution. This ranking is intended to be a helpful amendment of other available institutional rankings.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2146-2148
  7. Bornmann, L.; Bauer, J.: Which of the world's institutions employ the most highly cited researchers : an analysis of the data from highlycited.com (2015) 0.00 
    0.0047346456 = product of:
  0.014203936 = sum of:
    0.014203936 = product of:
      0.028407872 = sum of:
        0.028407872 = weight(_text_:of in 2223) [ClassicSimilarity], result of:
          0.028407872 = score(doc=2223,freq=18.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.41465375 = fieldWeight in 2223, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0625 = fieldNorm(doc=2223)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    In 2014, Thomson Reuters published a list of the most highly cited researchers worldwide (highlycited.com). Because the data are freely available for downloading and include the names of the researchers' institutions, we produced a ranking of the institutions on the basis of the number of highly cited researchers per institution. This ranking is intended to be a helpful amendment of other available institutional rankings.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2146-2148
  8. Leydesdorff, L.; Bornmann, L.; Mutz, R.; Opthof, T.: Turning the tables on citation analysis one more time : principles for comparing sets of documents (2011) 0.00 
    0.0045843013 = product of:
  0.013752903 = sum of:
    0.013752903 = product of:
      0.027505806 = sum of:
        0.027505806 = weight(_text_:of in 4485) [ClassicSimilarity], result of:
          0.027505806 = score(doc=4485,freq=30.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.4014868 = fieldWeight in 4485, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=4485)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks, the citation score of each paper is rated in terms of its percentile in the citation distribution. The percentile ranks approach allows for the formulation of a more abstract indicator scheme that can be used to organize and/or schematize different impact indicators according to three degrees of freedom: the selection of the reference sets, the evaluation criteria, and the choice of whether or not to define the publication sets as independent. Bibliometric data of seven principal investigators (PIs) of the Academic Medical Center of the University of Amsterdam are used as an exemplary dataset. We demonstrate that the proposed family indicators [R(6), R(100), R(6, k), R(100, k)] are an improvement on averages-based indicators because one can account for the shape of the distributions of citations over papers.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1370-1381
  9. Bornmann, L.: What is societal impact of research and how can it be assessed? : a literature survey (2013) 0.00 
    0.004428855 = product of:
  0.013286565 = sum of:
    0.013286565 = product of:
      0.02657313 = sum of:
        0.02657313 = weight(_text_:of in 606) [ClassicSimilarity], result of:
          0.02657313 = score(doc=606,freq=28.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.38787308 = fieldWeight in 606, product of:
              5.2915025 = tf(freq=28.0), with freq of:
                28.0 = termFreq=28.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=606)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Since the 1990s, the scope of research evaluations becomes broader as the societal products (outputs), societal use (societal references), and societal benefits (changes in society) of research come into scope. Society can reap the benefits of successful research studies only if the results are converted into marketable and consumable products (e.g., medicaments, diagnostic tools, machines, and devices) or services. A series of different names have been introduced which refer to the societal impact of research: third stream activities, societal benefits, societal quality, usefulness, public values, knowledge transfer, and societal relevance. What most of these names are concerned with is the assessment of social, cultural, environmental, and economic returns (impact and effects) from results (research output) or products (research outcome) of publicly funded research. This review intends to present existing research on and practices employed in the assessment of societal impact in the form of a literature survey. The objective is for this review to serve as a basis for the development of robust and reliable methods of societal impact measurement.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.217-233
  10. Leydesdorff, L.; Radicchi, F.; Bornmann, L.; Castellano, C.; Nooy, W. de: Field-normalized impact factors (IFs) : a comparison of rescaling and fractionally counted IFs (2013) 0.00 
    0.004267752 = product of:
  0.012803256 = sum of:
    0.012803256 = product of:
      0.025606511 = sum of:
        0.025606511 = weight(_text_:of in 1108) [ClassicSimilarity], result of:
          0.025606511 = score(doc=1108,freq=26.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.37376386 = fieldWeight in 1108, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=1108)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Two methods for comparing impact factors and citation rates across fields of science are tested against each other using citations to the 3,705 journals in the Science Citation Index 2010 (CD-Rom version of SCI) and the 13 field categories used for the Science and Engineering Indicators of the U.S. National Science Board. We compare (a) normalization by counting citations in proportion to the length of the reference list (1/N of references) with (b) rescaling by dividing citation scores by the arithmetic mean of the citation rate of the cluster. Rescaling is analytical and therefore independent of the quality of the attribution to the sets, whereas fractional counting provides an empirical strategy for normalization among sets (by evaluating the between-group variance). By the fairness test of Radicchi and Castellano (), rescaling outperforms fractional counting of citations for reasons that we consider.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2299-2309
  11. Bornmann, L.; Marx, W.: ¬The wisdom of citing scientists (2014) 0.00 
    0.004142815 = product of:
  0.012428444 = sum of:
    0.012428444 = product of:
      0.024856888 = sum of:
        0.024856888 = weight(_text_:of in 1293) [ClassicSimilarity], result of:
          0.024856888 = score(doc=1293,freq=18.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.36282203 = fieldWeight in 1293, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1293)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    This Brief Communication discusses the benefits of citation analysis in research evaluation based on Galton's "Wisdom of Crowds" (1907). Citations are based on the assessment of many which is why they can be considered to have some credibility. However, we show that citations are incomplete assessments and that one cannot assume that a high number of citations correlates with a high level of usefulness. Only when one knows that a rarely cited paper has been widely read is it possible to say-strictly speaking-that it was obviously of little use for further research. Using a comparison with "like" data, we try to determine that cited reference analysis allows for a more meaningful analysis of bibliometric data than times-cited analysis.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1288-1292
  12. Bornmann, L.: ¬The reception of publications by scientists in the early days of modern science (2014) 0.00 
    0.0041003237 = product of:
  0.01230097 = sum of:
    0.01230097 = product of:
      0.02460194 = sum of:
        0.02460194 = weight(_text_:of in 1509) [ClassicSimilarity], result of:
          0.02460194 = score(doc=1509,freq=6.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.3591007 = fieldWeight in 1509, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.09375 = fieldNorm(doc=1509)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.10, S.2160-2161
  13. Marx, W.; Bornmann, L.; Cardona, M.: Reference standards and reference multipliers for the comparison of the citation impact of papers published in different time periods (2010) 0.00 
    0.003945538 = product of:
  0.0118366135 = sum of:
    0.0118366135 = product of:
      0.023673227 = sum of:
        0.023673227 = weight(_text_:of in 3998) [ClassicSimilarity], result of:
          0.023673227 = score(doc=3998,freq=32.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34554482 = fieldWeight in 3998, product of:
              5.656854 = tf(freq=32.0), with freq of:
                32.0 = termFreq=32.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3998)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    In this study, reference standards and reference multipliers are suggested as a means to compare the citation impact of earlier research publications in physics (from the period of "Little Science" in the early 20th century) with that of contemporary papers (from the period of "Big Science," beginning around 1960). For the development of time-specific reference standards, the authors determined (a) the mean citation rates of papers in selected physics journals as well as (b) the mean citation rates of all papers in physics published in 1900 (Little Science) and in 2000 (Big Science); this was accomplished by relying on the processes of field-specific standardization in bibliometry. For the sake of developing reference multipliers with which the citation impact of earlier papers can be adjusted to the citation impact of contemporary papers, they combined the reference standards calculated for 1900 and 2000 into their ratio. The use of reference multipliers is demonstrated by means of two examples involving the time adjusted h index values for Max Planck and Albert Einstein.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.2061-20690
  14. Leydesdorff, L.; Bornmann, L.: Integrated impact indicators compared with impact factors : an alternative research design with policy implications (2011) 0.00 
    0.003945538 = product of:
  0.0118366135 = sum of:
    0.0118366135 = product of:
      0.023673227 = sum of:
        0.023673227 = weight(_text_:of in 4919) [ClassicSimilarity], result of:
          0.023673227 = score(doc=4919,freq=32.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34554482 = fieldWeight in 4919, product of:
              5.656854 = tf(freq=32.0), with freq of:
                32.0 = termFreq=32.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4919)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    In bibliometrics, the association of "impact" with central-tendency statistics is mistaken. Impacts add up, and citation curves therefore should be integrated instead of averaged. For example, the journals MIS Quarterly and Journal of the American Society for Information Science and Technology differ by a factor of 2 in terms of their respective impact factors (IF), but the journal with the lower IF has the higher impact. Using percentile ranks (e.g., top-1%, top-10%, etc.), an Integrated Impact Indicator (I3) can be based on integration of the citation curves, but after normalization of the citation curves to the same scale. The results across document sets can be compared as percentages of the total impact of a reference set. Total number of citations, however, should not be used instead because the shape of the citation curves is then not appreciated. I3 can be applied to any document set and any citation window. The results of the integration (summation) are fully decomposable in terms of journals or institutional units such as nations, universities, and so on because percentile ranks are determined at the paper level. In this study, we first compare I3 with IFs for the journals in two Institute for Scientific Information subject categories ("Information Science & Library Science" and "Multidisciplinary Sciences"). The library and information science set is additionally decomposed in terms of nations. Policy implications of this possible paradigm shift in citation impact analysis are specified.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.11, S.2133-2146
  15. Bornmann, L.: How much does the expected number of citations for a publication change if it contains the address of a specific scientific institute? : a new approach for the analysis of citation data on the institutional level based on regression models (2016) 0.00 
    0.003945538 = product of:
  0.0118366135 = sum of:
    0.0118366135 = product of:
      0.023673227 = sum of:
        0.023673227 = weight(_text_:of in 3095) [ClassicSimilarity], result of:
          0.023673227 = score(doc=3095,freq=32.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34554482 = fieldWeight in 3095, product of:
              5.656854 = tf(freq=32.0), with freq of:
                32.0 = termFreq=32.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3095)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Citation data for institutes are generally provided as numbers of citations or as relative citation rates (as, for example, in the Leiden Ranking). These numbers can then be compared between the institutes. This study aims to present a new approach for the evaluation of citation data at the institutional level, based on regression models. As example data, the study includes all articles and reviews from the Web of Science for the publication year 2003 (n?=?886,416 papers). The study is based on an in-house database of the Max Planck Society. The study investigates how much the expected number of citations for a publication changes if it contains the address of an institute. The calculation of the expected values allows, on the one hand, investigating how the citation impact of the papers of an institute appears in comparison with the total of all papers. On the other hand, the expected values for several institutes can be compared with one another or with a set of randomly selected publications. Besides the institutes, the regression models include factors which can be assumed to have a general influence on citation counts (e.g., the number of authors).
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2274-2282
  16. Bornmann, L.; Marx, W.: Distributions instead of single numbers : percentiles and beam plots for the assessment of single researchers (2014) 0.00 
    0.0039058835 = product of:
  0.01171765 = sum of:
    0.01171765 = product of:
      0.0234353 = sum of:
        0.0234353 = weight(_text_:of in 1190) [ClassicSimilarity], result of:
          0.0234353 = score(doc=1190,freq=16.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34207192 = fieldWeight in 1190, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1190)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Citations measure an aspect of scientific quality: the impact of publications (A.F.J. van Raan, 1996). Percentiles normalize the impact of papers with respect to their publication year and field without using the arithmetic average. They are suitable for visualizing the performance of a single scientist. Beam plots make it possible to present the distributions of percentiles in the different publication years combined with the medians from these percentiles within each year and across all years.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.1, S.206-208
  17. Marx, W.; Bornmann, L.; Barth, A.; Leydesdorff, L.: Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS) (2014) 0.00 
    0.0039058835 = product of:
  0.01171765 = sum of:
    0.01171765 = product of:
      0.0234353 = sum of:
        0.0234353 = weight(_text_:of in 1238) [ClassicSimilarity], result of:
          0.0234353 = score(doc=1238,freq=16.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34207192 = fieldWeight in 1238, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1238)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    We introduce the quantitative method named "Reference Publication Year Spectroscopy" (RPYS). With this method one can determine the historical roots of research fields and quantify their impact on current research. RPYS is based on the analysis of the frequency with which references are cited in the publications of a specific research field in terms of the publication years of these cited references. The origins show up in the form of more or less pronounced peaks mostly caused by individual publications that are cited particularly frequently. In this study, we use research on graphene and on solar cells to illustrate how RPYS functions, and what results it can deliver.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.4, S.751-764
  18. Bornmann, L.; Mutz, R.: Growth rates of modern science : a bibliometric analysis based on the number of publications and cited references (2015) 0.00 
    0.0038202507 = product of:
  0.011460752 = sum of:
    0.011460752 = product of:
      0.022921504 = sum of:
        0.022921504 = weight(_text_:of in 2261) [ClassicSimilarity], result of:
          0.022921504 = score(doc=2261,freq=30.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.33457235 = fieldWeight in 2261, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2261)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Many studies (in information science) have looked at the growth of science. In this study, we reexamine the question of the growth of science. To do this we (a) use current data up to publication year 2012 and (b) analyze the data across all disciplines and also separately for the natural sciences and for the medical and health sciences. Furthermore, the data were analyzed with an advanced statistical technique-segmented regression analysis-which can identify specific segments with similar growth rates in the history of science. The study is based on two different sets of bibliometric data: (a) the number of publications held as source items in the Web of Science (WoS, Thomson Reuters) per publication year and (b) the number of cited references in the publications of the source items per cited reference year. We looked at the rate at which science has grown since the mid-1600s. In our analysis of cited references we identified three essential growth phases in the development of science, which each led to growth rates tripling in comparison with the previous phase: from less than 1% up to the middle of the 18th century, to 2 to 3% up to the period between the two world wars, and 8 to 9% to 2010.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2215-2222
  19. Bornmann, L.: Is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration? : an analysis based on data from F1000Prime and normalized citation scores (2017) 0.00 
    0.0038202507 = product of:
  0.011460752 = sum of:
    0.011460752 = product of:
      0.022921504 = sum of:
        0.022921504 = weight(_text_:of in 3539) [ClassicSimilarity], result of:
          0.022921504 = score(doc=3539,freq=30.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.33457235 = fieldWeight in 3539, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3539)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    In recent years, the relationship of collaboration among scientists and the citation impact of papers have been frequently investigated. Most of the studies show that the two variables are closely related: An increasing collaboration activity (measured in terms of number of authors, number of affiliations, and number of countries) is associated with an increased citation impact. However, it is not clear whether the increased citation impact is based on the higher quality of papers that profit from more than one scientist giving expert input or other (citation-specific) factors. Thus, the current study addresses this question by using two comprehensive data sets with publications (in the biomedical area) including quality assessments by experts (F1000Prime member scores) and citation data for the publications. The study is based on more than 15,000 papers. Robust regression models are used to investigate the relationship between number of authors, number of affiliations, and number of countries, respectively, and citation impact-controlling for the papers' quality (measured by F1000Prime expert ratings). The results point out that the effect of collaboration activities on impact is largely independent of the papers' quality. The citation advantage is apparently not quality related; citation-specific factors (e.g., self-citations) seem to be important here.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.4, S.1036-1047
  20. Bornmann, L.: Interrater reliability and convergent validity of F1000Prime peer review (2015) 0.00 
    0.003743066 = product of:
  0.0112291975 = sum of:
    0.0112291975 = product of:
      0.022458395 = sum of:
        0.022458395 = weight(_text_:of in 2328) [ClassicSimilarity], result of:
          0.022458395 = score(doc=2328,freq=20.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.32781258 = fieldWeight in 2328, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=2328)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Peer review is the backbone of modern science. F1000Prime is a postpublication peer review system of the biomedical literature (papers from medical and biological journals). This study is concerned with the interrater reliability and convergent validity of the peer recommendations formulated in the F1000Prime peer review system. The study is based on about 100,000 papers with recommendations from faculty members. Even if intersubjectivity plays a fundamental role in science, the analyses of the reliability of the F1000Prime peer review system show a rather low level of agreement between faculty members. This result is in agreement with most other studies that have been published on the journal peer review system. Logistic regression models are used to investigate the convergent validity of the F1000Prime peer review system. As the results show, the proportion of highly cited papers among those selected by the faculty members is significantly higher than expected. In addition, better recommendation scores are also associated with higher performing papers.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2415-2426

Authors

Themes