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  • × author_ss:"Bornmann, L."
  1. Marx, W.; Bornmann, L.; Barth, A.; Leydesdorff, L.: Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS) (2014) 0.07 
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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.
  2. Bornmann, L.; Marx, W.: ¬The wisdom of citing scientists (2014) 0.03 
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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.
  3. 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) 0.03 
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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).
  4. 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) 0.03 
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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.
  5. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.02 
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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
  6. Bornmann, L.: What is societal impact of research and how can it be assessed? : a literature survey (2013) 0.02 
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    Abstract
    Since the 1990s, the scope of research evaluations becomes broader as the societal products (outputs), societal use (societal references), and societal benefits (changes in society) of research come into scope. Society can reap the benefits of successful research studies only if the results are converted into marketable and consumable products (e.g., medicaments, diagnostic tools, machines, and devices) or services. A series of different names have been introduced which refer to the societal impact of research: third stream activities, societal benefits, societal quality, usefulness, public values, knowledge transfer, and societal relevance. What most of these names are concerned with is the assessment of social, cultural, environmental, and economic returns (impact and effects) from results (research output) or products (research outcome) of publicly funded research. This review intends to present existing research on and practices employed in the assessment of societal impact in the form of a literature survey. The objective is for this review to serve as a basis for the development of robust and reliable methods of societal impact measurement.
  7. Bornmann, L.; Daniel, H.-D.: Multiple publication on a single research study: does it pay? : The influence of number of research articles on total citation counts in biomedicine (2007) 0.01 
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    Abstract
    Scientists may seek to report a single definable body of research in more than one publication, that is, in repeated reports of the same work or in fractional reports, in order to disseminate their research as widely as possible in the scientific community. Up to now, however, it has not been examined whether this strategy of "multiple publication" in fact leads to greater reception of the research. In the present study, we investigate the influence of number of articles reporting the results of a single study on reception in the scientific community (total citation counts of an article on a single study). Our data set consists of 96 applicants for a research fellowship from the Boehringer Ingelheim Fonds (BIF), an international foundation for the promotion of basic research in biomedicine. The applicants reported to us all articles that they had published within the framework of their doctoral research projects. On this single project, the applicants had published from 1 to 16 articles (M = 4; Mdn = 3). The results of a regression model with an interaction term show that the practice of multiple publication of research study results does in fact lead to greater reception of the research (higher total citation counts) in the scientific community. However, reception is dependent upon length of article: the longer the article, the more total citation counts increase with the number of articles. Thus, it pays for scientists to practice multiple publication of study results in the form of sizable reports.
  8. 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) 0.01 
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    Abstract
    In recent years, a number of studies have introduced methods for identifying papers with delayed recognition (so called "sleeping beauties," SBs) or have presented single publications as cases of SBs. Most recently, Ke, Ferrara, Radicchi, and Flammini (2015, Proceedings of the National Academy of Sciences of the USA, 112(24), 7426-7431) proposed the so called "beauty coefficient" (denoted as B) to quantify how much a given paper can be considered as a paper with delayed recognition. In this study, the new term smart girl (SG) is suggested to differentiate instant credit or "flashes in the pan" from SBs. Although SG and SB are qualitatively defined, the dynamic citation angle ß is introduced in this study as a simple way for identifying SGs and SBs quantitatively - complementing the beauty coefficient B. The citation angles for all articles from 1980 (n?=?166,870) in natural sciences are calculated for identifying SGs and SBs and their extent. We reveal that about 3% of the articles are typical SGs and about 0.1% typical SBs. The potential advantages of the citation angle approach are explained.
  9. Bornmann, L.; Marx, W.: Distributions instead of single numbers : percentiles and beam plots for the assessment of single researchers (2014) 0.01 
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  10. Bornmann, L.; Mutz, R.; Daniel, H.-D.: Are there better indices for evaluation purposes than the h index? : a comparison of nine different variants of the h index using data from biomedicine (2008) 0.01 
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    Abstract
    In this study, we examined empirical results on the h index and its most important variants in order to determine whether the variants developed are associated with an incremental contribution for evaluation purposes. The results of a factor analysis using bibliographic data on postdoctoral researchers in biomedicine indicate that regarding the h index and its variants, we are dealing with two types of indices that load on one factor each. One type describes the most productive core of a scientist's output and gives the number of papers in that core. The other type of indices describes the impact of the papers in the core. Because an index for evaluative purposes is a useful yardstick for comparison among scientists if the index corresponds strongly with peer assessments, we calculated a logistic regression analysis with the two factors resulting from the factor analysis as independent variables and peer assessment of the postdoctoral researchers as the dependent variable. The results of the regression analysis show that peer assessments can be predicted better using the factor impact of the productive core than using the factor quantity of the productive core.
  11. 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) 0.01 
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  12. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.01 
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    Date
    18. 3.2014 19:13:22
  13. 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
  14. 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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    Date
    8. 1.2019 18:22:45
  15. 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
  16. 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) 0.00 
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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.
  17. 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%.
  18. 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).
  19. Bornmann, L.: Is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration? : an analysis based on data from F1000Prime and normalized citation scores (2017) 0.00 
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    Abstract
    In recent years, the relationship of collaboration among scientists and the citation impact of papers have been frequently investigated. Most of the studies show that the two variables are closely related: An increasing collaboration activity (measured in terms of number of authors, number of affiliations, and number of countries) is associated with an increased citation impact. However, it is not clear whether the increased citation impact is based on the higher quality of papers that profit from more than one scientist giving expert input or other (citation-specific) factors. Thus, the current study addresses this question by using two comprehensive data sets with publications (in the biomedical area) including quality assessments by experts (F1000Prime member scores) and citation data for the publications. The study is based on more than 15,000 papers. Robust regression models are used to investigate the relationship between number of authors, number of affiliations, and number of countries, respectively, and citation impact-controlling for the papers' quality (measured by F1000Prime expert ratings). The results point out that the effect of collaboration activities on impact is largely independent of the papers' quality. The citation advantage is apparently not quality related; citation-specific factors (e.g., self-citations) seem to be important here.
  20. 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) 0.00 
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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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