Search (62 results, page 1 of 4)

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Abstract

Fields of technoscience like biotechnology develop in a network mode: disciplinary insights from different backgrounds are recombined as competing innovation systems are continuously reshaped. The ongoing process of integration at the European level generates an additional network of transnational collaborations. Using the title words of scientific publications in five core journals of biotechnology, multivariate analysis is used to distinguish between the intellectual organization of the publications in terms of title words and the institutional network in terms of addresses of documents. The interaction among the representation of intellectual space in terms of words and co-words, and the potentially European network system is compared with the document sets with American and Japanese addresses. The European system can also be decomposed in terms of the contributions of member states. Whereas a European vocabulary can be made visible at the global level, this communality disappears by this decomposition. The network effect at the European level can be considered as institutional more than cognitive

Footnote

Vgl. auch die Stellungnahme von P. van den Besselaar: Empirical evidence of self-organization? in: JASIST 54(2003) no.1, S.87-90.

Source

Journal of the American Society for Information Science and technology. 52(2001) no.14, S.1262-1274

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Abstract

When using scientific literature to model scholarly discourse, a research specialty can be operationalized as an evolving set of related documents. Each publication can be expected to contribute to the further development of the specialty at the research front. The specific combinations of title words and cited references in a paper can then be considered as a signature of the knowledge claim in the paper: New words and combinations of words can be expected to represent variation, while each paper is at the same time selectively positioned into the intellectual organization of a field using context-relevant references. Can the mutual information among these three dimensions - title words, cited references, and sequence numbers - be used as an indicator of the extent to which intellectual organization structures the uncertainty prevailing at a research front? The effect of the discovery of nanotubes (1991) on the previously existing field of fullerenes is used as a test case. Thereafter, this method is applied to science studies with a focus on scientometrics using various sample delineations. An emerging research front about citation analysis can be indicated.

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2488-2498

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Abstract

Aggregated journal-journal citations can be used for mapping the intellectual organization of the sciences in terms of specialties because the latter can be considered as interreading communities. Can the journal-journal citations also be used as early indicators of change by comparing the files for two subsequent years? Probabilistic entropy measures enable us to analyze changes in large datasets at different levels of aggregation and in considerable detail. Compares Journal Citation Reports of the Social Science Citation Index for 1999 with similar data for 1998 and analyzes the differences using these measures. Compares the various indicators with similar developments in the Science Citation Index. Specialty formation seems a more important mechanism in the development of the social sciences than in the natural and life sciences, but the developments in the social sciences are volatile. The use of aggregate statistics based on the Science Citation Index is ill-advised in the case of the social sciences because of structural differences in the underlying dynamics.

Date

6.11.2005 19:02:22

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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.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.10, S.1582-1597

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Abstract

Logarithmic transformation of the data has been recommended by the literature in the case of highly skewed distributions such as those commonly found in information science. The purpose of the transformation is to make the data conform to the lognormal law of error for inferential purposes. How does this transformation affect the analysis? We factor analyze and visualize the citation environment of the Journal of the American Chemical Society (JACS) before and after a logarithmic transformation. The transformation strongly reduces the variance necessary for classificatory purposes and therefore is counterproductive to the purposes of the descriptive statistics. We recommend against the logarithmic transformation when sets cannot be defined unambiguously. The intellectual organization of the sciences is reflected in the curvilinear parts of the citation distributions while negative powerlaws fit excellently to the tails of the distributions.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.11, S.1470-1486

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Abstract

International co-authorship relations and university-industry-government (Triple Helix) relations have hitherto been studied separately. Using Japanese publication data for the 1981-2004 period, we were able to study both kinds of relations in a single design. In the Japanese file, 1,277,030 articles with at least one Japanese address were attributed to the three sectors, and we know additionally whether these papers were coauthored internationally. Using the mutual information in three and four dimensions, respectively, we show that the Japanese Triple-Helix system has been continuously eroded at the national level. However, since the mid-1990s, international coauthorship relations have contributed to a reduction of the uncertainty at the national level. In other words, the national publication system of Japan has developed a capacity to retain surplus value generated internationally. In a final section, we compare these results with an analysis based on similar data for Canada. A relative uncoupling of national university-industry-government relations because of international collaborations is indicated in both countries.

Date

22. 3.2009 19:07:20

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.778-788

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Abstract

Methods developed for mapping the journal structure contained in aggregated journal-journal citations in the Science Citation Index (SCI; Thomson ISI, 2002) are applied to the Chinese Science Citation Database of the Chinese Academy of Sciences. This database covered 991 journals in 2001, of which only 37 originally had English titles; only 31 of which were covered by the SCI. Using factor-analytical and graph-analytical techniques, the authors show that the journal relations are dually structured. The main structure is the intellectual organization of the journals in journal groups (as in the international SCI), but the university-based journals provide an institutional layer that orients this structure towards practical ends (e.g., agriculture). This mechanism of integration is further distinguished from the role of general science journals. The Chinese Science Citation Database thus exhibits the characteristics of "Mode 2" or transdisciplinary science in the production of scientific knowledge more than its Western counterpart does. The contexts of application lead to correlation among the components.

Source

Journal of the American Society for Information Science and Technology. 56(2005) no.14, S.1469-1479

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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 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

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Abstract

Portfolio analysis of the publication profile of a unit of interest, ranging from individuals and organizations to a scientific field or interdisciplinary programs, aims to inform analysts and decision makers about the position of the unit, where it has been, and where it may go in a complex adaptive environment. A portfolio analysis may aim to identify the gap between the current position of an organization and a goal that it intends to achieve or identify competencies of multiple institutions. We introduce a new visual analytic method for analyzing, comparing, and contrasting characteristics of publication portfolios. The new method introduces a novel design of dual-map thematic overlays on global maps of science. Each publication portfolio can be added as one layer of dual-map overlays over 2 related, but distinct, global maps of science: one for citing journals and the other for cited journals. We demonstrate how the new design facilitates a portfolio analysis in terms of patterns emerging from the distributions of citation threads and the dynamics of trajectories as a function of space and time. We first demonstrate the analysis of portfolios defined on a single source article. Then we contrast publication portfolios of multiple comparable units of interest; namely, colleges in universities and corporate research organizations. We also include examples of overlays of scientific fields. We expect that our method will provide new insights to portfolio analysis.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.2, S.334-351

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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.

Source

Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.769-772

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Source

Journal of the American Society for Information Science and Technology. 63(2012) no.11, S.2349-2350

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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.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.3, S.707-714

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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

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

Can the inclusion of new journals in the Science Citation Index be used for the indication of structural change in the database, and how can this change be compared with reorganizations of reiations among previously included journals? Change in the number of journals (n) is distinguished from change in the number of journal categories (m). Although the number of journals can be considered as a given at each moment in time, the number of journal categories is based an a reconstruction that is time-stamped ex post. The reflexive reconstruction is in need of an update when new information becomes available in a next year. Implications of this shift towards an evolutionary perspective are specified.

Source

Journal of the American Society for Information Science and technology. 53(2002) no.12, S.987-994

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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.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.12, S.1616-1628

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Abstract

With the program HistCite(TM) it is possible to generate and visualize the most relevant papers in a set of documents retrieved from the Science Citation Index. Historical reconstructions of scientific developments can be represented chronologically as developments in networks of citation relations extracted from scientific literature. This study aims to go beyond the historical reconstruction of scientific knowledge, enriching the output of HistCiteTM with algorithms from social-network analysis and information theory. Using main-path analysis, it is possible to highlight the structural backbone in the development of a scientific field. The expected information value of the message can be used to indicate whether change in the distribution (of citations) has occurred to such an extent that a path-dependency is generated. This provides us with a measure of evolutionary change between subsequent documents. The forgetting and rewriting of historically prior events at the research front can thus be indicated. These three methods - HistCite, main path and path dependent transitions - are applied to a set of documents related to fullerenes and the fullerene-like structures known as nanotubes.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1948-1962

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Abstract

Problem solving often requires crossing boundaries, such as those between disciplines. When policy-makers call for "interdisciplinarity," however, they often mean "synergy." Synergy is generated when the whole offers more possibilities than the sum of its parts. An increase in the number of options above the sum of the options in subsets can be measured as redundancy; that is, the number of not-yet-realized options. The number of options available to an innovation system for realization can be as decisive for the system's survival as the historically already-realized innovations. Unlike "interdisciplinarity," "synergy" can also be generated in sectorial or geographical collaborations. The measurement of "synergy," however, requires a methodology different from the measurement of "interdisciplinarity." In this study, we discuss recent advances in the operationalization and measurement of "interdisciplinarity," and propose a methodology for measuring "synergy" based on information theory. The sharing of meanings attributed to information from different perspectives can increase redundancy. Increasing redundancy reduces the relative uncertainty, for example, in niches. The operationalization of the two concepts-"interdisciplinarity" and "synergy"-as different and partly overlapping indicators allows for distinguishing between the effects and the effectiveness of science-policy interventions in research priorities.

Source

Journal of the Association for Information Science and Technology. 72(2021) no.4, S.387-402

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Abstract

In addition to science citation indicators of journals like impact and immediacy, social network analysis provides a set of centrality measures like degree, betweenness, and closeness centrality. These measures are first analyzed for the entire set of 7,379 journals included in the Journal Citation Reports of the Science Citation Index and the Social Sciences Citation Index 2004 (Thomson ISI, Philadelphia, PA), and then also in relation to local citation environments that can be considered as proxies of specialties and disciplines. Betweenness centrality is shown to be an indicator of the interdisciplinarity of journals, but only in local citation environments and after normalization; otherwise, the influence of degree centrality (size) overshadows the betweenness-centrality measure. The indicator is applied to a variety of citation environments, including policy-relevant ones like biotechnology and nanotechnology. The values of the indicator remain sensitive to the delineations of the set because of the indicator's local character. Maps showing interdisciplinarity of journals in terms of betweenness centrality can be drawn using information about journal citation environments, which is available online.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1303-1319