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  • × author_ss:"Leydesdorff, L."
  • × year_i:[2000 TO 2010}
  1. Leydesdorff, L.; Heimeriks, G.: ¬The self-organization of the European information society : the case of "biotechnology" (2001) 0.00
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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
    Type
    a
  2. Leydesdorff, L.; Vaughan, L.: Co-occurrence matrices and their applications in information science : extending ACA to the Web environment (2006) 0.00
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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.
    Type
    a
  3. Leydesdorff, L.; Bensman, S.: Classification and Powerlaws : the logarithmic transformation (2006) 0.00
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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.
    Type
    a
  4. Leydesdorff, L.: Patent classifications as indicators of intellectual organization (2008) 0.00
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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.
    Type
    a
  5. Leydesdorff, L.; Bihui, J.: Mapping the Chinese Science Citation Database in terms of aggregated journal-journal citation relations (2005) 0.00
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    Type
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  6. Leydesdorff, L.: On the normalization and visualization of author co-citation data : Salton's Cosine versus the Jaccard index (2008) 0.00
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  7. Leydesdorff, L.: Caveats for the use of citation indicators in research and journal evaluations (2008) 0.00
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  8. Leydesdorff, L.; Schank, T.: Dynamic animations of journal maps : indicators of structural changes and interdisciplinary developments (2008) 0.00
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  9. Bensman, S.J.; Leydesdorff, L.: Definition and identification of journals as bibliographic and subject entities : librarianship versus ISI Journal Citation Reports methods and their effect on citation measures (2009) 0.00
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  10. Leydesdorff, L.: How are new citation-based journal indicators adding to the bibliometric toolbox? (2009) 0.00
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