-
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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- Date
- 22. 1.2011 12:51:07
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
-
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
-
Bornmann, L.; Bauer, J.; Haunschild, R.: Distribution of women and men among highly cited scientists (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2715-2716
-
Bornmann, L.: What do altmetrics counts mean? : a plea for content analyses (2016)
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- Date
- 19. 3.2016 12:40:15
-
Besselaar, P. van den; Wagner, C,; Bornmann, L.: Correct assumptions? (2016)
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- Date
- 14. 6.2016 12:03:02
-
Leydesdorff, L.; Wagner, C,; Bornmann, L.: Replicability and the public/private divide (2016)
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- Date
- 14. 6.2016 12:01:54
-
Bornmann, L.: Nature's top 100 revisited (2015)
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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.
-
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
-
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
-
Bornmann, L.: Lässt sich die Qualität von Forschung messen? (2013)
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- Series
- Fortschritte in der Wissensorganisation; Bd.12
- Source
- Wissen - Wissenschaft - Organisation: Proceedings der 12. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation Bonn, 19. bis 21. Oktober 2009. Hrsg.: H.P. Ohly
-
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)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2711-2713
-
Bornmann, L.: Interrater reliability and convergent validity of F1000Prime peer review (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2415-2426
-
Bornmann, L.; Haunschild, R.: Overlay maps based on Mendeley data : the use of altmetrics for readership networks (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3064-3072
-
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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- Date
- 28. 9.2010 12:50:25
-
Leydesdorff, L.; Bornmann, L.: Integrated impact indicators compared with impact factors : an alternative research design with policy implications (2011)
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- Date
- 12. 2.2012 17:53:51
-
Bornmann, L.; Marx, W.: ¬The Anna Karenina principle : a way of thinking about success in science (2012)
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- Date
- 3.10.2012 11:51:12
-
Ye, F.Y.; Bornmann, L.: "Smart girls" versus "sleeping beauties" in the sciences : the identification of instant and delayed recognition by using the citation angle (2018)
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- Date
- 12. 2.2018 18:48:57
-
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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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3095-3100
-
Bornmann, L.; Haunschild, R.: ¬An empirical look at the nature index (2017)
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- Abstract
- In November 2014, the Nature Index (NI) was introduced (see http://www.natureindex.com) by the Nature Publishing Group (NPG). The NI comprises the primary research articles published in the past 12 months in a selection of reputable journals. Starting from two short comments on the NI (Haunschild & Bornmann, 2015a, 2015b), we undertake an empirical analysis of the NI using comprehensive country data. We investigate whether the huge efforts of computing the NI are justified and whether the size-dependent NI indicators should be complemented by size-independent variants. The analysis uses data from the Max Planck Digital Library in-house database (which is based on Web of Science data) and from the NPG. In the first step of the analysis, we correlate the NI with other metrics that are simpler to generate than the NI. The resulting large correlation coefficients point out that the NI produces similar results as simpler solutions. In the second step of the analysis, relative and size-independent variants of the NI are generated that should be additionally presented by the NPG. The size-dependent NI indicators favor large countries (or institutions) and the top-performing small countries (or institutions) do not come into the picture.
