Search (59 results, page 1 of 3)

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Abstract

Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3064-3072

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Abstract

The BRICS countries (Brazil, Russia, India, China, and South Africa) are notable for their increasing participation in science and technology. The governments of these countries have been boosting their investments in research and development to become part of the group of nations doing research at a world-class level. This study investigates the development of the BRICS countries in the domain of top-cited papers (top 10% and 1% most frequently cited papers) between 1990 and 2010. To assess the extent to which these countries have become important players at the top level, we compare the BRICS countries with the top-performing countries worldwide. As the analyses of the (annual) growth rates show, with the exception of Russia, the BRICS countries have increased their output in terms of most frequently cited papers at a higher rate than the top-cited countries worldwide. By way of additional analysis, we generate coauthorship networks among authors of highly cited papers for 4 time points to view changes in BRICS participation (1995, 2000, 2005, and 2010). Here, the results show that all BRICS countries succeeded in becoming part of this network, whereby the Chinese collaboration activities focus on the US.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.7, S.1507-1513

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Abstract

According to current research in bibliometrics, percentiles (or percentile rank classes) are the most suitable method for normalizing the citation counts of individual publications in terms of the subject area, the document type, and the publication year. Up to now, bibliometric research has concerned itself primarily with the calculation of percentiles. This study suggests how percentiles (and percentile rank classes) can be analyzed meaningfully for an evaluation study. Publication sets from four universities are compared with each other to provide sample data. These suggestions take into account on the one hand the distribution of percentiles over the publications in the sets (universities here) and on the other hand concentrate on the range of publications with the highest citation impact-that is, the range that is usually of most interest in the evaluation of scientific performance.

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

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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

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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.

Source

Journal of the Association for Information Science and Technology. 70(2019) no.5, S.509-525

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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.

Series

Advances in information science

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.217-233

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Source

Journal of the American Society for Information Science and Technology. 64(2013) no.6, S.1306-1308

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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.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.4, S.751-764

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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

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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.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.8, S.1100-1107

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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

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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.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2321-2339

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Source

Journal of the Association for Information Science and Technology. 66(2015) no.8, S.1738-1739

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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

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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.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1288-1292

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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

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Abstract

The first sentence of Leo Tolstoy's (1875-1877/2001) novel Anna Karenina is: "Happy families are all alike; every unhappy family is unhappy in its own way." Here, Tolstoy means that for a family to be happy, several key aspects must be given (e.g., good health of all family members, acceptable financial security, and mutual affection). If there is a deficiency in any one or more of these key aspects, the family will be unhappy. In this article, we introduce the Anna Karenina principle as a way of thinking about success in science in three central areas in (modern) science: (a) peer review of research grant proposals and manuscripts (money and journal space as scarce resources), (b) citation of publications (reception as a scarce resource), and (c) new scientific discoveries (recognition as a scarce resource). If resources are scarce at the highly competitive research front (journal space, funds, reception, and recognition), there can be success only when several key prerequisites for the allocation of the resources are fulfilled. If any one of these prerequisites is not fulfilled, the grant proposal, manuscript submission, the published paper, or the discovery will not be successful.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.10, S.2037-2051

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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.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.2061-20690

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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

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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