Search (26 results, page 1 of 2)

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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

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Abstract

Citation analysis of documents retrieved from the Medline database (at the Web of Knowledge) has been possible only on a case-by-case basis. A technique is presented here for citation analysis in batch mode using both Medical Subject Headings (MeSH) at the Web of Knowledge and the Science Citation Index at the Web of Science (WoS). This freeware routine is applied to the case of "Brugada Syndrome," a specific disease and field of research (since 1992). The journals containing these publications, for example, are attributed to WoS categories other than "cardiac and cardiovascular systems", perhaps because of the possibility of genetic testing for this syndrome in the clinic. With this routine, all the instruments available for citation analysis can now be used on the basis of MeSH terms. Other options for crossing between Medline, WoS, and Scopus are also reviewed.

Object

Web of Knowledge

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Abstract

We present a novel routine, namely medlineR, based on the R language, that allows the user to match data from Medline/PubMed with records indexed in the ISI Web of Science (WoS) database. The matching allows exploiting the rich and controlled vocabulary of medical subject headings (MeSH) of Medline/PubMed with additional fields of WoS. The integration provides data (e.g., citation data, list of cited reference, list of the addresses of authors' host organizations, WoS subject categories) to perform a variety of scientometric analyses. This brief communication describes medlineR, the method on which it relies, and the steps the user should follow to perform the matching across the two databases. To demonstrate the differences from Leydesdorff and Opthof (Journal of the American Society for Information Science and Technology, 64(5), 1076-1080), we conclude this artcle by testing the routine on the MeSH category "Burgada syndrome."

Object

Web of Science

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Abstract

Using Web of Science data, portfolio analysis in terms of journal coverage can be projected onto a base map for units of analysis such as countries, cities, universities, and firms. The units of analysis under study can be compared statistically across the 10,000+ journals. The interdisciplinarity of the portfolios is measured using Rao-Stirling diversity or Zhang et?al.'s improved measure 2D3. At the country level we find regional differentiation (e.g., Latin American or Asian countries), but also a major divide between advanced and less-developed countries. Israel and Israeli cities outperform other nations and cities in terms of diversity. Universities appear to be specifically related to firms when a number of these units are exploratively compared. The instrument is relatively simple and straightforward, and one can generalize the application to any document set retrieved from the Web of Science (WoS). Further instruction is provided online at http://www.leydesdorff.net/portfolio.

Aid

Web of Science

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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

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Date

29. 9.2018 11:22:09

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Abstract

Co-occurrence matrices, such as cocitation, coword, and colink matrices, have been used widely in the information sciences. However, confusion and controversy have hindered the proper statistical analysis of these data. The underlying problem, in our opinion, involved understanding the nature of various types of matrices. This article discusses the difference between a symmetrical cocitation matrix and an asymmetrical citation matrix as well as the appropriate statistical techniques that can be applied to each of these matrices, respectively. Similarity measures (such as the Pearson correlation coefficient or the cosine) should not be applied to the symmetrical cocitation matrix but can be applied to the asymmetrical citation matrix to derive the proximity matrix. The argument is illustrated with examples. The study then extends the application of co-occurrence matrices to the Web environment, in which the nature of the available data and thus data collection methods are different from those of traditional databases such as the Science Citation Index. A set of data collected with the Google Scholar search engine is analyzed by using both the traditional methods of multivariate analysis and the new visualization software Pajek, which is based on social network analysis and graph theory.

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Abstract

Using the option Analyze Results with the Web of Science, one can directly generate overlays onto global journal maps of science. The maps are based on the 10,000+ journals contained in the Journal Citation Reports (JCR) of the Science and Social Sciences Citation Indices (2011). The disciplinary diversity of the retrieval is measured in terms of Rao-Stirling's "quadratic entropy" (Izsák & Papp, 1995). Since this indicator of interdisciplinarity is normalized between 0 and 1, interdisciplinarity can be compared among document sets and across years, cited or citing. The colors used for the overlays are based on Blondel, Guillaume, Lambiotte, and Lefebvre's (2008) community-finding algorithms operating on the relations among journals included in the JCR. The results can be exported from VOSViewer with different options such as proportional labels, heat maps, or cluster density maps. The maps can also be web-started or animated (e.g., using PowerPoint). The "citing" dimension of the aggregated journal-journal citation matrix was found to provide a more comprehensive description than the matrix based on the cited archive. The relations between local and global maps and their different functions in studying the sciences in terms of journal literatures are further discussed: Local and global maps are based on different assumptions and can be expected to serve different purposes for the explanation.

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Object

Web of science

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Abstract

Via the Internet, information scientists can obtain costfree access to large databases in the "hidden" or "deep Web." These databases are often structured far more than the Internet domains themselves. The patent database of the U.S. Patent and Trade Office is used in this study to examine the science base of patents in terms of the literature references in these patents. Universitybased patents at the global level are compared with results when using the national economy of the Netherlands as a system of reference. Methods for accessing the online databases and for the visualization of the results are specified. The conclusion is that "biotechnology" has historically generated a model for theorizing about university-industry relations that cannot easily be generalized to other sectors and disciplines.

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Abstract

The debate about which similarity measure one should use for the normalization in the case of Author Co-citation Analysis (ACA) is further complicated when one distinguishes between the symmetrical co-citation - or, more generally, co-occurrence - matrix and the underlying asymmetrical citation - occurrence - matrix. In the Web environment, the approach of retrieving original citation data is often not feasible. In that case, one should use the Jaccard index, but preferentially after adding the number of total citations (i.e., occurrences) on the main diagonal. Unlike Salton's cosine and the Pearson correlation, the Jaccard index abstracts from the shape of the distributions and focuses only on the intersection and the sum of the two sets. Since the correlations in the co-occurrence matrix may be spurious, this property of the Jaccard index can be considered as an advantage in this case.

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Abstract

The possibilities of using the Arts & Humanities Citation Index (A&HCI) for journal mapping have not been sufficiently recognized because of the absence of a Journal Citations Report (JCR) for this database. A quasi-JCR for the A&HCI ([2008]) was constructed from the data contained in the Web of Science and is used for the evaluation of two journals as examples: Leonardo and Art Journal. The maps on the basis of the aggregated journal-journal citations within this domain can be compared with maps including references to journals in the Science Citation Index and Social Science Citation Index. Art journals are cited by (social) science journals more than by other art journals, but these journals draw upon one another in terms of their own references. This cultural impact in terms of being cited is not found when documents with a topic such as digital humanities are analyzed. This community of practice functions more as an intellectual organizer than a journal.

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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.

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Abstract

Using data from the Web of Science (WoS), we analyze the mutual information among university, industry, and government addresses (U-I-G) at the country level for a number of countries. The dynamic evolution of the Triple Helix can thus be compared among developed and developing nations in terms of cross-sectional coauthorship relations. The results show that the Triple Helix interactions among the three subsystems U-I-G become less intensive over time, but unequally for different countries. We suggest that globalization erodes local Triple Helix relations and thus can be expected to have increased differentiation in national systems since the mid-1990s. This effect of globalization is more pronounced in developed countries than in developing ones. In the dynamic analysis, we focus on a more detailed comparison between China and the United States. Specifically, the Chinese Academy of the (Social) Sciences is changing increasingly from a public research institute to an academic one, and this has a measurable effect on China's position in the globalization.

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Abstract

"Citation classics" are not only highly cited, but also cited during several decades. We explore whether the peaks in the spectrograms generated by Reference Publication Years Spectroscopy (RPYS) indicate such long-term impact by comparing across RPYS for subsequent time intervals. Multi-RPYS enables us to distinguish between short-term citation peaks at the research front that decay within 10 years versus historically constitutive (long-term) citations that function as concept symbols. Using these constitutive citations, one is able to cluster document sets (e.g., journals) in terms of intellectually shared histories. We test this premise by clustering 40 journals in the Web of Science Category of Information and Library Science using multi-RPYS. It follows that RPYS can not only be used for retrieving roots of sets under study (cited), but also for algorithmic historiography of the citing sets. Significant references are historically rooted symbols among other citations that function as currency.

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Abstract

Using Scopus data, we construct a global map of science based on aggregated journal-journal citations from 1996-2012 (N of journals?=?20,554). This base map enables users to overlay downloads from Scopus interactively. Using a single year (e.g., 2012), results can be compared with mappings based on the Journal Citation Reports at the Web of Science (N?=?10,936). The Scopus maps are more detailed at both the local and global levels because of their greater coverage, including, for example, the arts and humanities. The base maps can be interactively overlaid with journal distributions in sets downloaded from Scopus, for example, for the purpose of portfolio analysis. Rao-Stirling diversity can be used as a measure of interdisciplinarity in the sets under study. Maps at the global and the local level, however, can be very different because of the different levels of aggregation involved. Two journals, for example, can both belong to the humanities in the global map, but participate in different specialty structures locally. The base map and interactive tools are available online (with instructions) at http://www.leydesdorff.net/scopus_ovl.

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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.

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Date

2. 2.2010 19:29:29

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12. 7.2008 18:46:29

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22. 5.2003 19:48:04