Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 04. Juni 2021)
1Mutz, R. ; Wolbring, T. ; Daniel, H.-D.: ¬The effect of the "very important paper" (VIP) designation in Angewandte Chemie International Edition on citation impact : a propensity score matching analysis.
In: Journal of the Association for Information Science and Technology. 68(2017) no.9, S.2139-2153.
Abstract: Scientific journals publish an increasing number of articles every year. To steer readers' attention to the most important papers, journals use several techniques (e.g., lead paper). Angewandte Chemie International Edition (AC), a leading international journal in chemistry, signals high-quality papers through designating them as a "very important paper" (VIP). This study aims to investigate the citation impact of Communications in AC receiving the special feature VIP, both cumulated and over time. Using propensity score matching, treatment group (VIP) and control group (non-VIP) were balanced for 14 covariates to estimate the unconfounded "average treatment effect on the treated" for the VIP designation. Out of N = 3,011 Communications published in 2007 and 2008, N = 207 received the special feature VIP. For each Communication, data were collected from AC (e.g., referees' ratings) and from the databases Chemical Abstracts (e.g., sections) and the Web of Science (e.g., citations). The estimated unconfounded average treatment effect on the treated (that is, Communications designated as a VIP) was statistically significant and amounted to 19.83 citations. In addition, the special feature VIP fostered the cumulated annual citation growth. For instance, the time until a Communication reached its maximum annual number of citations, was reduced.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23825/full.
2Mutz, R. ; Daniel, H.-D.: What is behind the curtain of the Leiden Ranking?.
In: Journal of the Association for Information Science and Technology. 66(2015) no.9, S.1950-1953.
Abstract: Even with very well-documented rankings of universities, it is difficult for an individual university to reconstruct its position in the ranking. What is the reason behind whether a university places higher or lower in the ranking? Taking the example of ETH Zurich, the aim of this communication is to reconstruct how the high position of ETHZ (in Europe rank no. 1 in PP[top 10%]) in the Centre for Science and Technology Studies (CWTS) Leiden Ranking 2013 in the field "social sciences, arts and humanities" came about. According to our analyses, the bibliometric indicator values of a university depend very strongly on weights that result in differing estimates of both the total number of a university's publications and the number of publications with a citation impact in the 90th percentile, or PP(top 10%). In addition, we examine the effect of weights at the level of individual publications. Based on the results, we offer recommendations for improving the Leiden Ranking (for example, publication of sample calculations to increase transparency).
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23360/abstract.
3Bornmann, L. ; Mutz, R.: Growth rates of modern science : a bibliometric analysis based on the number of publications and cited references.
In: Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2215-2222.
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.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23329/abstract.
4Mutz, 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.
In: Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2321-2339.
Abstract: It is essential for research funding organizations to ensure both the validity and fairness of the grant approval procedure. The ex-ante peer evaluation (EXANTE) of N?=?8,496 grant applications submitted to the Austrian Science Fund from 1999 to 2009 was statistically analyzed. For 1,689 funded research projects an ex-post peer evaluation (EXPOST) was also available; for the rest of the grant applications a multilevel missing data imputation approach was used to consider verification bias for the first time in peer-review research. Without imputation, the predictive validity of EXANTE was low (r?=?.26) but underestimated due to verification bias, and with imputation it was r?=?.49. That is, the decision-making procedure is capable of selecting the best research proposals for funding. In the EXANTE there were several potential biases (e.g., gender). With respect to the EXPOST there was only one real bias (discipline-specific and year-specific differential prediction). The novelty of this contribution is, first, the combining of theoretical concepts of validity and fairness with a missing data imputation approach to correct for verification bias and, second, multilevel modeling to test peer review-based funding decisions for both validity and fairness in terms of potential and real biases.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23315/abstract.
5Bornmann, L. ; Mutz, R.: From P100 to P100' : a new citation-rank approach.
In: Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943.
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.
Themenfeld: Informetrie ; Retrievalalgorithmen
6Bornmann, L. ; Mutz, R. ; Daniel, H.-D.: Multilevel-statistical reformulation of citation-based university rankings : the Leiden ranking 2011/2012.
In: Journal of the American Society for Information Science and Technology. 64(2013) no.8, S.1649-1658.
Abstract: Since the 1990s, with the heightened competition and the strong growth of the international higher education market, an increasing number of rankings have been created that measure the scientific performance of an institution based on data. The Leiden Ranking 2011/2012 (LR) was published early in 2012. Starting from Goldstein and Spiegelhalter's (1996) recommendations for conducting quantitative comparisons among institutions, in this study we undertook a reformulation of the LR by means of multilevel regression models. First, with our models we replicated the ranking results; second, the reanalysis of the LR data showed that only 5% of the PPtop10% total variation is attributable to differences between universities. Beyond that, about 80% of the variation between universities can be explained by differences among countries. If covariates are included in the model the differences among most of the universities become meaningless. Our findings have implications for conducting university rankings in general and for the LR in particular. For example, with Goldstein-adjusted confidence intervals, it is possible to interpret the significance of differences among universities meaningfully: Rank differences among universities should be interpreted as meaningful only if their confidence intervals do not overlap.
7Bornmann, L. ; Moya Anegón, F. de ; Mutz, R.: Do universities or research institutions with a specific subject profile have an advantage or a disadvantage in institutional rankings?.
In: Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2310-2316.
Abstract: Using data compiled for the SCImago Institutions Ranking, we look at whether the subject area type an institution (university or research-focused institution) belongs to (in terms of the fields researched) has an influence on its ranking position. We used latent class analysis to categorize institutions based on their publications in certain subject areas. Even though this categorization does not relate directly to scientific performance, our results show that it exercises an important influence on the outcome of a performance measurement: Certain subject area types of institutions have an advantage in the ranking positions when compared with others. This advantage manifests itself not only when performance is measured with an indicator that is not field-normalized but also for indicators that are field-normalized.
8Leydesdorff, L. ; Bornmann, L. ; Mutz, R. ; Opthof, T.: Turning the tables on citation analysis one more time : principles for comparing sets of documents.
In: Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1370-1381.
Abstract: We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks, the citation score of each paper is rated in terms of its percentile in the citation distribution. The percentile ranks approach allows for the formulation of a more abstract indicator scheme that can be used to organize and/or schematize different impact indicators according to three degrees of freedom: the selection of the reference sets, the evaluation criteria, and the choice of whether or not to define the publication sets as independent. Bibliometric data of seven principal investigators (PIs) of the Academic Medical Center of the University of Amsterdam are used as an exemplary dataset. We demonstrate that the proposed family indicators [R(6), R(100), R(6, k), R(100, k)] are an improvement on averages-based indicators because one can account for the shape of the distributions of citations over papers.
9Bornmann, L. ; Mutz, R. ; Daniel, H.D.: Do we need the h index and its variants in addition to standard bibliometric measures?.
In: Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1286-1289.
Abstract: In this study, we investigate whether there is a need for the h index and its variants in addition to standard bibliometric measures (SBMs). Results from our recent study (L. Bornmann, R. Mutz, & H.-D. Daniel, 2008) have indicated that there are two types of indices: One type of indices (e.g., h index) describes the most productive core of a scientist's output and informs about the number of papers in the core. The other type of indices (e.g., a index) depicts the impact of the papers in the core. In evaluative bibliometric studies, the two dimensions quantity and quality of output are usually assessed using the SBMs number of publications (for the quantity dimension) and total citation counts (for the impact dimension). We additionally included the SBMs into the factor analysis. The results of the newly calculated analysis indicate that there is a high intercorrelation between number of publications and the indices that load substantially on the factor Quantity of the Productive Core as well as between total citation counts and the indices that load substantially on the factor Impact of the Productive Core. The high-loading indices and SBMs within one performance dimension could be called redundant in empirical application, as high intercorrelations between different indicators are a sign for measuring something similar (or the same). Based on our findings, we propose the use of any pair of indicators (one relating to the number of papers in a researcher's productive core and one relating to the impact of these core papers) as a meaningful approach for comparing scientists.
10Bornmann, 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.
In: Journal of the American Society for Information Science and Technology. 59(2008) no.5, S.830-837.
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.