Search (27 results, page 1 of 2)

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Abstract

This paper explores the ISI Journal Citation Reports (JCR) bibliographic and subject structures through Library of Congress (LC) and American research libraries cataloging and classification methodology. The 2006 Science Citation Index JCR Behavioral Sciences subject category journals are used as an example. From the library perspective, the main fault of the JCR bibliographic structure is that the JCR mistakenly identifies journal title segments as journal bibliographic entities, seriously affecting journal rankings by total cites and the impact factor. In respect to JCR subject structure, the title segment, which constitutes the JCR bibliographic basis, is posited as the best bibliographic entity for the citation measurement of journal subject relationships. Through factor analysis and other methods, the JCR subject categorization of journals is tested against their LC subject headings and classification. The finding is that JCR and library journal subject analyses corroborate, clarify, and correct each other.

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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

The aggregated journal-journal citation matrix derived from Journal Citation Reports 2001 can be decomposed into a unique subject classification using the graph-analytical algorithm of bi-connected components. This technique was recently incorporated in software tools for social network analysis. The matrix can be assessed in terms of its decomposability using articulation points which indicate overlap between the components. The articulation points of this set did not exhibit a next-order network of "general science" journals. However, the clusters differ in size and in terms of the internal density of their relations. A full classification of the journals is provided in the Appendix. The clusters can also be extracted and mapped for the visualization.

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Abstract

The aggregated journal-journal citation matrix - based on the Journal Citation Reports (JCR) of the Science Citation Index - can be decomposed by indexers or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two content-based classifications of journals: the ISI Subject Categories and the field/subfield classification of Glänzel and Schubert (2003). The content-based schemes allow for the attribution of more than a single category to a journal, whereas the algorithms maximize the ratio of within-category citations over between-category citations in the aggregated category-category citation matrix. By adding categories, indexers generate between-category citations, which may enrich the database, for example, in the case of inter-disciplinary developments. Algorithmic decompositions, on the other hand, are more heavily skewed towards a relatively small number of categories, while this is deliberately counter-acted upon in the case of content-based classifications. Because of the indexer effects, science policy studies and the sociology of science should be careful when using content-based classifications, which are made for bibliographic disclosure, and not for the purpose of analyzing latent structures in scientific communications. Despite the large differences among them, the four classification schemes enable us to generate surprisingly similar maps of science at the global level. Erroneous classifications are cancelled as noise at the aggregate level, but may disturb the evaluation locally.

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Abstract

The decomposition of scientific literature into disciplinary and subdisciplinary structures is one of the core goals of scientometrics. How can we achieve a good decomposition? The ISI subject categories classify journals included in the Science Citation Index (SCI). The aggregated journal-journal citation matrix contained in the Journal Citation Reports can be aggregated on the basis of these categories. This leads to an asymmetrical matrix (citing versus cited) that is much more densely populated than the underlying matrix at the journal level. Exploratory factor analysis of the matrix of subject categories suggests a 14-factor solution. This solution could be interpreted as the disciplinary structure of science. The nested maps of science (corresponding to 14 factors, 172 categories, and 6,164 journals) are online at http://www.leydesdorff.net/map06. Presumably, inaccuracies in the attribution of journals to the ISI subject categories average out so that the factor analysis reveals the main structures. The mapping of science could, therefore, be comprehensive and reliable on a large scale albeit imprecise in terms of the attribution of journals to the ISI subject categories.

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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

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Abstract

A journal set in an interdisciplinary or newly developing area can be determined by including the journals classified under the most relevant ISI Subject Categories into a journal-journal citation matrix. Despite the fuzzy character of borders, factor analysis of the citation patterns enables us to delineate the specific set by discarding the noise. This methodology is illustrated using communication studies as a hybrid development between political science and social psychology. The development can be visualized using animations which support the claim that a specific journal set in communication studies is increasingly developing, notably in the being cited patterns. The resulting set of 28 journals in communication studies is smaller and more focused than the 45 journals classified by the ISI Subject Categories as Communication. The proposed method is tested for its robustness by extending the relevant environments to sets including many more journals.

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Abstract

Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the MEDLINE database. Focusing on three main branches-"diseases," "drugs and chemicals," and "techniques and equipment"-we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the MEDLINE database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the MEDLINE database on one hand, and the Science Citation Index and Scopus (containing citation information) on the other.

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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.

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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."

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Abstract

The use of Pearson's correlation coefficient in Author Cocitation Analysis was compared with Salton's cosine measure in a number of recent contributions. Unlike the Pearson correlation, the cosine is insensitive to the number of zeros. However, one has the option of applying a logarithmic transformation in correlation analysis. Information caiculus is based an both the logarithmic transformation and provides a non-parametric statistics. Using this methodology, one can cluster a document set in a precise way and express the differences in terms of bits of information. The algorithm is explained and used an the data set, which was made the subject of this discussion.

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Abstract

We argue that the communication structures in the Chinese social sciences have not yet been sufficiently reformed. Citation patterns among Chinese domestic journals in three subject areas - political science and Marxism, library and information science, and economics - are compared with their counterparts internationally. Like their colleagues in the natural and life sciences, Chinese scholars in the social sciences provide fewer references to journal publications than their international counterparts; like their international colleagues, social scientists provide fewer references than natural sciences. The resulting citation networks, therefore, are sparse. Nevertheless, the citation structures clearly suggest that the Chinese social sciences are far less specialized in terms of disciplinary delineations than their international counterparts. Marxism studies are more established than political science in China. In terms of the impact of the Chinese political system on academic fields, disciplines closely related to the political system are less specialized than those weakly related. In the discussion section, we explore reasons that may cause the current stagnation and provide policy recommendations.

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Abstract

Grasping the fruits of "emerging technologies" is an objective of many government priority programs in a knowledge-based and globalizing economy. We use the publication records (in the Science Citation Index) of two emerging technologies to study the mechanisms of diffusion in the case of two innovation trajectories: small interference RNA (siRNA) and nanocrystalline solar cells (NCSC). Methods for analyzing and visualizing geographical and cognitive diffusion are specified as indicators of different dynamics. Geographical diffusion is illustrated with overlays to Google Maps; cognitive diffusion is mapped using an overlay to a map based on the ISI subject categories. The evolving geographical networks show both preferential attachment and small-world characteristics. The strength of preferential attachment decreases over time while the network evolves into an oligopolistic control structure with small-world characteristics. The transition from disciplinary-oriented ("Mode 1") to transfer-oriented ("Mode 2") research is suggested as the crucial difference in explaining the different rates of diffusion between siRNA and NCSC.

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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

Using the Arts & Humanities Citation Index (A&HCI) 2008, we apply mapping techniques previously developed for mapping journal structures in the Science and Social Sciences Citation Indices. Citation relations among the 110,718 records were aggregated at the level of 1,157 journals specific to the A&HCI, and the journal structures are questioned on whether a cognitive structure can be reconstructed and visualized. Both cosine-normalization (bottom up) and factor analysis (top down) suggest a division into approximately 12 subsets. The relations among these subsets are explored using various visualization techniques. However, we were not able to retrieve this structure using the Institute for Scientific Information Subject Categories, including the 25 categories that are specific to the A&HCI. We discuss options for validation such as against the categories of the Humanities Indicators of the American Academy of Arts and Sciences, the panel structure of the European Reference Index for the Humanities, and compare our results with the curriculum organization of the Humanities Section of the College of Letters and Sciences of the University of California at Los Angeles as an example of institutional organization.

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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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Abstract

Using the 138,751 patents filed in 2006 under the Patent Cooperation Treaty, co-classification analysis is pursued on the basis of three- and four-digit codes in the International Patent Classification (IPC, 8th ed.). The co-classifications among the patents enable us to analyze and visualize the relations among technologies at different levels of aggregation. The hypothesis that classifications might be considered as the organizers of patents into classes, and therefore that co-classification patterns - more than co-citation patterns - might be useful for mapping, is not corroborated. The classifications hang weakly together, even at the four-digit level; at the country level, more specificity can be made visible. However, countries are not the appropriate units of analysis because patent portfolios are largely similar in many advanced countries in terms of the classes attributed. Instead of classes, one may wish to explore the mapping of title words as a better approach to visualize the intellectual organization of patents.

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Date

22. 5.2003 19:48:04

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Date

6.11.2005 19:02:22

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Date

22. 3.2009 19:07:20