Search (44 results, page 1 of 3)

  • × author_ss:"Bornmann, L."
  • × theme_ss:"Informetrie"
  • × type_ss:"a"
  1. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.04 
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    Date
    18. 3.2014 19:13:22
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.4, S.866-867
    Type
    a
  2. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.03 
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    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
    Type
    a
  3. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.02 
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    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
    Type
    a
  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 
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    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
    Type
    a
  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 
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    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
    Type
    a
  6. Bornmann, L.: Is there currently a scientific revolution in Scientometrics? (2014) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.3, S.647-648
    Type
    a
  7. Bornmann, L.: What do altmetrics counts mean? : a plea for content analyses (2016) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.4, S.1016-1017
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  8. Bornmann, L.: Nature's top 100 revisited (2015) 0.01 
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    Content
    Bezug: Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2714. Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23554/abstract.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2166
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  9. Bornmann, L.: On the function of university rankings (2014) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.2, S.428-429
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  10. Bornmann, L.; Bauer, J.; Haunschild, R.: Distribution of women and men among highly cited scientists (2015) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2715-2716
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  11. 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) 0.01 
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    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
    Type
    a
  12. 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) 0.01 
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    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
    Type
    a
  13. Bornmann, L.; Marx, W.: ¬The wisdom of citing scientists (2014) 0.01 
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    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
    Type
    a
  14. Bornmann, L.; Daniel, H.-D.: What do we know about the h index? (2007) 0.01 
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    Abstract
    Jorge Hirsch recently proposed the h index to quantify the research output of individual scientists. The new index has attracted a lot of attention in the scientific community. The claim that the h index in a single number provides a good representation of the scientific lifetime achievement of a scientist as well as the (supposed) simple calculation of the h index using common literature databases lead to the danger of improper use of the index. We describe the advantages and disadvantages of the h index and summarize the studies on the convergent validity of this index. We also introduce corrections and complements as well as single-number alternatives to the h index.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1381-1385
    Type
    a
  15. Bornmann, L.; Leydesdorff, L.: Which cities produce more excellent papers than can be expected? : a new mapping approach, using Google Maps, based on statistical significance testing (2011) 0.01 
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    Abstract
    The methods presented in this paper allow for a statistical analysis revealing centers of excellence around the world using programs that are freely available. Based on Web of Science data (a fee-based database), field-specific excellence can be identified in cities where highly cited papers were published more frequently than can be expected. Compared to the mapping approaches published hitherto, our approach is more analytically oriented by allowing the assessment of an observed number of excellent papers for a city against the expected number. Top performers in output are cities in which authors are located who publish a statistically significant higher number of highly cited papers than can be expected for these cities. As sample data for physics, chemistry, and psychology show, these cities do not necessarily have a high output of highly cited papers.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.10, S.1954-1962
    Type
    a
  16. Bornmann, L.: How well does a university perform in comparison with its peers? : The use of odds, and odds ratios, for the comparison of institutional citation impact using the Leiden Rankings (2015) 0.01 
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    Abstract
    This study presents the calculation of odds, and odds ratios, for the comparison of the citation impact of universities in the Leiden Ranking. Odds and odds ratios can be used to measure the performance difference between a selected university and competing institutions, or the average of selected competitors, in a relatively simple but clear way.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2711-2713
    Type
    a
  17. Leydesdorff, L.; Bornmann, L.: Integrated impact indicators compared with impact factors : an alternative research design with policy implications (2011) 0.01 
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    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
    Type
    a
  18. Bauer, J.; Leydesdorff, L.; Bornmann, L.: Highly cited papers in Library and Information Science (LIS) : authors, institutions, and network structures (2016) 0.01 
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    Abstract
    As a follow-up to the highly cited authors list published by Thomson Reuters in June 2014, we analyzed the top 1% most frequently cited papers published between 2002 and 2012 included in the Web of Science (WoS) subject category "Information Science & Library Science." In all, 798 authors contributed to 305 top 1% publications; these authors were employed at 275 institutions. The authors at Harvard University contributed the largest number of papers, when the addresses are whole-number counted. However, Leiden University leads the ranking if fractional counting is used. Twenty-three of the 798 authors were also listed as most highly cited authors by Thomson Reuters in June 2014 (http://highlycited.com/). Twelve of these 23 authors were involved in publishing 4 or more of the 305 papers under study. Analysis of coauthorship relations among the 798 highly cited scientists shows that coauthorships are based on common interests in a specific topic. Three topics were important between 2002 and 2012: (a) collection and exploitation of information in clinical practices; (b) use of the Internet in public communication and commerce; and (c) scientometrics.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3095-3100
    Type
    a
  19. Bornmann, L.; Daniel, H.-D.: Universality of citation distributions : a validation of Radicchi et al.'s relative indicator cf = c/c0 at the micro level using data from chemistry (2009) 0.01 
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    Abstract
    In a recently published PNAS paper, Radicchi, Fortunato, and Castellano (2008) propose the relative indicator cf as an unbiased indicator for citation performance across disciplines (fields, subject areas). To calculate cf, the citation rate for a single paper is divided by the average number of citations for all papers in the discipline in which the single paper has been categorized. cf values are said to lead to a universality of discipline-specific citation distributions. Using a comprehensive dataset of an evaluation study on Angewandte Chemie International Edition (AC-IE), we tested the advantage of using this indicator in practical application at the micro level, as compared with (1) simple citation rates, and (2) z-scores, which have been used in psychological testing for many years for normalization of test scores. To calculate z-scores, the mean number of citations of the papers within a discipline is subtracted from the citation rate of a single paper, and the difference is then divided by the citations' standard deviation for a discipline. Our results indicate that z-scores are better suited than cf values to produce universality of discipline-specific citation distributions.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1664-1670
    Type
    a
  20. Marx, W.; Bornmann, L.; Barth, A.; Leydesdorff, L.: Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS) (2014) 0.01 
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    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
    Type
    a

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