Search (17 results, page 1 of 1)

  • × author_ss:"Bornmann, L."
  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. 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.
    Field
    Bibliothekswesen
    Informationswissenschaft
  2. Leydesdorff, L.; Bornmann, L.: ¬The operationalization of "fields" as WoS subject categories (WCs) in evaluative bibliometrics : the cases of "library and information science" and "science & technology studies" (2016) 0.01 
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    Field
    Bibliothekswesen
    Informationswissenschaft
  3. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.00 
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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
  4. Bornmann, L.: Lässt sich die Qualität von Forschung messen? (2013) 0.00 
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    Abstract
    Grundsätzlich können wir bei Bewertungen in der Wissenschaft zwischen einer 'qualitative' Form, der Bewertung einer wissenschaftlichen Arbeit (z. B. eines Manuskripts oder Forschungsantrags) durch kompetente Peers, und einer 'quantitative' Form, der Bewertung von wissenschaftlicher Arbeit anhand bibliometrischer Indikatoren unterscheiden. Beide Formen der Bewertung sind nicht unumstritten. Die Kritiker des Peer Review sehen vor allem zwei Schwächen des Verfahrens: (1) Verschiedene Gutachter würden kaum in der Bewertung ein und derselben wissenschaftlichen Arbeit übereinstimmen. (2) Gutachterliche Empfehlungen würden systematische Urteilsverzerrungen aufweisen. Gegen die Verwendung von Zitierhäufigkeiten als Indikator für die Qualität einer wissenschaftlichen Arbeit wird seit Jahren eine Vielzahl von Bedenken geäußert. Zitierhäufigkeiten seien keine 'objektiven' Messungen von wissenschaftlicher Qualität, sondern ein kritisierbares Messkonstrukt. So wird unter anderem kritisiert, dass wissenschaftliche Qualität ein komplexes Phänomen darstelle, das nicht auf einer eindimensionalen Skala (d. h. anhand von Zitierhäufigkeiten) gemessen werden könne. Es werden empirische Ergebnisse zur Reliabilität und Fairness des Peer Review Verfahrens sowie Forschungsergebnisse zur Güte von Zitierhäufigkeiten als Indikator für wissenschaftliche Qualität vorgestellt.
  5. Bornmann, L.; Marx, W.: Distributions instead of single numbers : percentiles and beam plots for the assessment of single researchers (2014) 0.00 
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    Date
    29. 1.2014 15:58:21
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.1, S.206-208
  6. Bornmann, L.; Schier, H.; Marx, W.; Daniel, H.-D.: Is interactive open access publishing able to identify high-impact submissions? : a study on the predictive validity of Atmospheric Chemistry and Physics by using percentile rank classes (2011) 0.00 
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    Date
    8. 1.2011 18:29:40
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.1, S.61-71
  7. Bornmann, L.: On the function of university rankings (2014) 0.00 
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    Date
    29. 1.2014 16:55:03
  8. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.00 
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    Date
    18. 3.2014 19:13:22
  9. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.00 
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    Date
    22. 8.2014 17:05:18
  10. 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) 0.00 
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    Date
    22. 3.2013 19:44:17
  11. 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) 0.00 
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    Date
    22. 1.2011 12:51:07
  12. Leydesdorff, L.; Zhou, P.; Bornmann, L.: How can journal impact factors be normalized across fields of science? : An assessment in terms of percentile ranks and fractional counts (2013) 0.00 
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    Abstract
    Using the CD-ROM version of the Science Citation Index 2010 (N = 3,705 journals), we study the (combined) effects of (a) fractional counting on the impact factor (IF) and (b) transformation of the skewed citation distributions into a distribution of 100 percentiles and six percentile rank classes (top-1%, top-5%, etc.). Do these approaches lead to field-normalized impact measures for journals? In addition to the 2-year IF (IF2), we consider the 5-year IF (IF5), the respective numerators of these IFs, and the number of Total Cites, counted both as integers and fractionally. These various indicators are tested against the hypothesis that the classification of journals into 11 broad fields by PatentBoard/NSF (National Science Foundation) provides statistically significant between-field effects. Using fractional counting the between-field variance is reduced by 91.7% in the case of IF5, and by 79.2% in the case of IF2. However, the differences in citation counts are not significantly affected by fractional counting. These results accord with previous studies, but the longer citation window of a fractionally counted IF5 can lead to significant improvement in the normalization across fields.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.1, S.96-107
  13. Bornmann, L.; Moya Anegón, F.de: What proportion of excellent papers makes an institution one of the best worldwide? : Specifying thresholds for the interpretation of the results of the SCImago Institutions Ranking and the Leiden Ranking (2014) 0.00 
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    Abstract
    University rankings generally present users with the problem of placing the results given for an institution in context. Only a comparison with the performance of all other institutions makes it possible to say exactly where an institution stands. In order to interpret the results of the SCImago Institutions Ranking (based on Scopus data) and the Leiden Ranking (based on Web of Science data), in this study we offer thresholds with which it is possible to assess whether an institution belongs to the top 1%, top 5%, top 10%, top 25%, or top 50% of institutions in the world. The thresholds are based on the excellence rate or PPtop 10%. Both indicators measure the proportion of an institution's publications which belong to the 10% most frequently cited publications and are the most important indicators for measuring institutional impact. For example, while an institution must achieve a value of 24.63% in the Leiden Ranking 2013 to be considered one of the top 1% of institutions worldwide, the SCImago Institutions Ranking requires 30.2%.
  14. 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 
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    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.
  15. Leydesdorff, L.; Bornmann, L.: Integrated impact indicators compared with impact factors : an alternative research design with policy implications (2011) 0.00 
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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.
  16. Bornmann, L.; Wagner, C.; Leydesdorff, L.: BRICS countries and scientific excellence : a bibliometric analysis of most frequently cited papers (2015) 0.00 
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    Abstract
    The BRICS countries (Brazil, Russia, India, China, and South Africa) are notable for their increasing participation in science and technology. The governments of these countries have been boosting their investments in research and development to become part of the group of nations doing research at a world-class level. This study investigates the development of the BRICS countries in the domain of top-cited papers (top 10% and 1% most frequently cited papers) between 1990 and 2010. To assess the extent to which these countries have become important players at the top level, we compare the BRICS countries with the top-performing countries worldwide. As the analyses of the (annual) growth rates show, with the exception of Russia, the BRICS countries have increased their output in terms of most frequently cited papers at a higher rate than the top-cited countries worldwide. By way of additional analysis, we generate coauthorship networks among authors of highly cited papers for 4 time points to view changes in BRICS participation (1995, 2000, 2005, and 2010). Here, the results show that all BRICS countries succeeded in becoming part of this network, whereby the Chinese collaboration activities focus on the US.
  17. Bornmann, L.; Mutz, R.: Growth rates of modern science : a bibliometric analysis based on the number of publications and cited references (2015) 0.00 
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    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.

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