Search (15 results, page 1 of 1)

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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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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.

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Abstract

All journals that use peer review have to deal with the following question: Does the peer review system fulfill its declared objective to select the best scientific work? We investigated the journal peer-review process at Angewandte Chemie International Edition (AC-IE), one of the prime chemistry journals worldwide, and conducted a citation analysis for Communications that were accepted by the journal (n = 878) or rejected but published elsewhere (n = 959). The results of negative binomial-regression models show that holding all other model variables constant, being accepted by AC-IE increases the expected number of citations by up to 50%. A comparison of average citation counts (with 95% confidence intervals) of accepted and rejected (but published elsewhere) Communications with international scientific reference standards was undertaken. As reference standards, (a) mean citation counts for the journal set provided by Thomson Reuters corresponding to the field chemistry and (b) specific reference standards that refer to the subject areas of Chemical Abstracts were used. When compared to reference standards, the mean impact on chemical research is for the most part far above average not only for accepted Communications but also for rejected (but published elsewhere) Communications. However, average and below-average scientific impact is to be expected significantly less frequently for accepted Communications than for rejected Communications. All in all, the results of this study confirm that peer review at AC-IE is able to select the best scientific work with the highest impact on chemical research.

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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.

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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.

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Abstract

Two methods for comparing impact factors and citation rates across fields of science are tested against each other using citations to the 3,705 journals in the Science Citation Index 2010 (CD-Rom version of SCI) and the 13 field categories used for the Science and Engineering Indicators of the U.S. National Science Board. We compare (a) normalization by counting citations in proportion to the length of the reference list (1/N of references) with (b) rescaling by dividing citation scores by the arithmetic mean of the citation rate of the cluster. Rescaling is analytical and therefore independent of the quality of the attribution to the sets, whereas fractional counting provides an empirical strategy for normalization among sets (by evaluating the between-group variance). By the fairness test of Radicchi and Castellano (), rescaling outperforms fractional counting of citations for reasons that we consider.

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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.

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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.

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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.

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Date

18. 3.2014 19:13:22

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Date

22. 8.2014 17:05:18

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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.

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Date

22. 3.2013 19:44:17

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Date

8. 1.2019 18:22:45

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Date

22. 1.2011 12:51:07