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  • × author_ss:"Bornmann, L."
  • × theme_ss:"Informetrie"
  1. 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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    Abstract
    Normalization of citation scores using reference sets based on Web of Science subject categories (WCs) has become an established ("best") practice in evaluative bibliometrics. For example, the Times Higher Education World University Rankings are, among other things, based on this operationalization. However, WCs were developed decades ago for the purpose of information retrieval and evolved incrementally with the database; the classification is machine-based and partially manually corrected. Using the WC "information science & library science" and the WCs attributed to journals in the field of "science and technology studies," we show that WCs do not provide sufficient analytical clarity to carry bibliometric normalization in evaluation practices because of "indexer effects." Can the compliance with "best practices" be replaced with an ambition to develop "best possible practices"? New research questions can then be envisaged.
    Aid
    Web of Science
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.3, S.707-714
  2. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.01 
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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
  3. 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
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.4, S.866-867
  4. Bauer, J.; Leydesdorff, L.; Bornmann, L.: Highly cited papers in Library and Information Science (LIS) : authors, institutions, and network structures (2016) 0.00 
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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
  5. 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) 0.00 
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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
  6. 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.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2215-2222
  7. 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%.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.4, S.732-736
  8. 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 
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    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
  9. 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) 0.00 
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    Abstract
    In the humanities and social sciences, bibliometric methods for the assessment of research performance are (so far) less common. This study uses a concrete example in an attempt to evaluate a research institute from the area of social sciences and humanities with the help of data from Google Scholar (GS). In order to use GS for a bibliometric study, we developed procedures for the normalization of citation impact, building on the procedures of classical bibliometrics. In order to test the convergent validity of the normalized citation impact scores, we calculated normalized scores for a subset of the publications based on data from the Web of Science (WoS) and Scopus. Even if scores calculated with the help of GS and the WoS/Scopus are not identical for the different publication types (considered here), they are so similar that they result in the same assessment of the institute investigated in this study: For example, the institute's papers whose journals are covered in the WoS are cited at about an average rate (compared with the other papers in the journals).
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.11, S.2778-2789
  10. Bornmann, L.; Haunschild, R.: ¬An empirical look at the nature index (2017) 0.00 
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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.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.3, S.653-659
  11. 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
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
  12. 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
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.587-595
  13. 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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    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
  14. Bornmann, L.: Nature's top 100 revisited (2015) 0.00 
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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
  15. Bornmann, L.: On the function of university rankings (2014) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.2, S.428-429
  16. Bornmann, L.: Is there currently a scientific revolution in Scientometrics? (2014) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.3, S.647-648
  17. Bornmann, L.; Bauer, J.; Haunschild, R.: Distribution of women and men among highly cited scientists (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2715-2716
  18. Bornmann, L.: What do altmetrics counts mean? : a plea for content analyses (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.4, S.1016-1017
  19. 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.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.11, S.2133-2146
  20. 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 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2146-2148

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