-
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)
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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
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Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
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Besselaar, P. van den; Wagner, C,; Bornmann, L.: Correct assumptions? (2016)
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-
Leydesdorff, L.; Wagner, C,; Bornmann, L.: Replicability and the public/private divide (2016)
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
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Collins, H.; Bornmann, L.: On scientific misconduct (2014)
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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)
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- Date
- 22. 3.2013 19:44:17
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Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019)
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- Date
- 8. 1.2019 18:22:45
-
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)
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-
Bornmann, L.; Marx, W.: ¬The Anna Karenina principle : a way of thinking about success in science (2012)
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- Abstract
- The first sentence of Leo Tolstoy's (1875-1877/2001) novel Anna Karenina is: "Happy families are all alike; every unhappy family is unhappy in its own way." Here, Tolstoy means that for a family to be happy, several key aspects must be given (e.g., good health of all family members, acceptable financial security, and mutual affection). If there is a deficiency in any one or more of these key aspects, the family will be unhappy. In this article, we introduce the Anna Karenina principle as a way of thinking about success in science in three central areas in (modern) science: (a) peer review of research grant proposals and manuscripts (money and journal space as scarce resources), (b) citation of publications (reception as a scarce resource), and (c) new scientific discoveries (recognition as a scarce resource). If resources are scarce at the highly competitive research front (journal space, funds, reception, and recognition), there can be success only when several key prerequisites for the allocation of the resources are fulfilled. If any one of these prerequisites is not fulfilled, the grant proposal, manuscript submission, the published paper, or the discovery will not be successful.
-
Bornmann, L.; Wagner, C.; Leydesdorff, L.: BRICS countries and scientific excellence : a bibliometric analysis of most frequently cited papers (2015)
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Bauer, J.; Leydesdorff, L.; Bornmann, L.: Highly cited papers in Library and Information Science (LIS) : authors, institutions, and network structures (2016)
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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.
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Leydesdorff, L.; Bornmann, L.; Mingers, J.: Statistical significance and effect sizes of differences among research universities at the level of nations and worldwide based on the Leiden rankings (2019)
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- Abstract
- The Leiden Rankings can be used for grouping research universities by considering universities which are not statistically significantly different as homogeneous sets. The groups and intergroup relations can be analyzed and visualized using tools from network analysis. Using the so-called "excellence indicator" PPtop-10%-the proportion of the top-10% most-highly-cited papers assigned to a university-we pursue a classification using (a) overlapping stability intervals, (b) statistical-significance tests, and (c) effect sizes of differences among 902 universities in 54 countries; we focus on the UK, Germany, Brazil, and the USA as national examples. Although the groupings remain largely the same using different statistical significance levels or overlapping stability intervals, these classifications are uncorrelated with those based on effect sizes. Effect sizes for the differences between universities are small (w < .2). The more detailed analysis of universities at the country level suggests that distinctions beyond three or perhaps four groups of universities (high, middle, low) may not be meaningful. Given similar institutional incentives, isomorphism within each eco-system of universities should not be underestimated. Our results suggest that networks based on overlapping stability intervals can provide a first impression of the relevant groupings among universities. However, the clusters are not well-defined divisions between groups of universities.
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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)
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-
Bornmann, L.: Lässt sich die Qualität von Forschung messen? (2013)
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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.
-
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)
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- 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.
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Bornmann, L.; Mutz, R.; Daniel, H.-D.: Multilevel-statistical reformulation of citation-based university rankings : the Leiden ranking 2011/2012 (2013)
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Mutz, R.; Bornmann, L.; Daniel, H.-D.: Testing for the fairness and predictive validity of research funding decisions : a multilevel multiple imputation for missing data approach using ex-ante and ex-post peer evaluation data from the Austrian science fund (2015)
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Bornmann, L.; Thor, A.; Marx, W.; Schier, H.: ¬The application of bibliometrics to research evaluation in the humanities and social sciences : an exploratory study using normalized Google Scholar data for the publications of a research institute (2016)
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