Search (31 results, page 1 of 2)

  • × author_ss:"Leydesdorff, L."
  1. Leydesdorff, L.: ¬The university-industry knowledge relationship : analyzing patents and the science base of technologies (2004) 0.06
    0.055277795 = product of:
      0.08291669 = sum of:
        0.055512875 = weight(_text_:reference in 2887) [ClassicSimilarity], result of:
          0.055512875 = score(doc=2887,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 2887, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=2887)
        0.027403818 = product of:
          0.054807637 = sum of:
            0.054807637 = weight(_text_:database in 2887) [ClassicSimilarity], result of:
              0.054807637 = score(doc=2887,freq=2.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.26797873 = fieldWeight in 2887, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2887)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    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.
  2. Rotolo, D.; Leydesdorff, L.: Matching Medline/PubMed data with Web of Science: A routine in R language (2015) 0.06
    0.055277795 = product of:
      0.08291669 = sum of:
        0.055512875 = weight(_text_:reference in 2224) [ClassicSimilarity], result of:
          0.055512875 = score(doc=2224,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 2224, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=2224)
        0.027403818 = product of:
          0.054807637 = sum of:
            0.054807637 = weight(_text_:database in 2224) [ClassicSimilarity], result of:
              0.054807637 = score(doc=2224,freq=2.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.26797873 = fieldWeight in 2224, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2224)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    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."
  3. Leydesdorff, L.; Bornmann, L.: ¬The operationalization of "fields" as WoS subject categories (WCs) in evaluative bibliometrics : the cases of "library and information science" and "science & technology studies" (2016) 0.06
    0.055277795 = product of:
      0.08291669 = sum of:
        0.055512875 = weight(_text_:reference in 2779) [ClassicSimilarity], result of:
          0.055512875 = score(doc=2779,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 2779, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=2779)
        0.027403818 = product of:
          0.054807637 = sum of:
            0.054807637 = weight(_text_:database in 2779) [ClassicSimilarity], result of:
              0.054807637 = score(doc=2779,freq=2.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.26797873 = fieldWeight in 2779, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2779)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    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.
  4. Hellsten, I.; Leydesdorff, L.: ¬The construction of interdisciplinarity : the development of the knowledge base and programmatic focus of the journal Climatic Change, 1977-2013 (2016) 0.04
    0.04226508 = product of:
      0.063397616 = sum of:
        0.046260733 = weight(_text_:reference in 3089) [ClassicSimilarity], result of:
          0.046260733 = score(doc=3089,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.22474778 = fieldWeight in 3089, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3089)
        0.017136881 = product of:
          0.034273762 = sum of:
            0.034273762 = weight(_text_:22 in 3089) [ClassicSimilarity], result of:
              0.034273762 = score(doc=3089,freq=2.0), product of:
                0.17717063 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.050593734 = queryNorm
                0.19345059 = fieldWeight in 3089, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3089)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    Abstract
    Climate change as a complex physical and social issue has gained increasing attention in the natural as well as the social sciences. Climate change research has become more interdisciplinary and even transdisciplinary as a typical Mode-2 science that is also dependent on an application context for its further development. We propose to approach interdisciplinarity as a co-construction of the knowledge base in the reference patterns and the programmatic focus in the editorials in the core journal of the climate-change sciences-Climatic Change-during the period 1977-2013. First, we analyze the knowledge base of the journal and map journal-journal relations on the basis of the references in the articles. Second, we follow the development of the programmatic focus by analyzing the semantics in the editorials. We argue that interdisciplinarity is a result of the co-construction between different agendas: The selection of publications into the knowledge base of the journal, and the adjustment of the programmatic focus to the political context in the editorials. Our results show a widening of the knowledge base from referencing the multidisciplinary journals Nature and Science to citing journals from specialist fields. The programmatic focus follows policy-oriented issues and incorporates public metaphors.
    Date
    24. 8.2016 17:53:22
  5. Marx, W.; Bornmann, L.; Barth, A.; Leydesdorff, L.: Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS) (2014) 0.03
    0.030530527 = product of:
      0.09159158 = sum of:
        0.09159158 = weight(_text_:reference in 1238) [ClassicSimilarity], result of:
          0.09159158 = score(doc=1238,freq=4.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.4449779 = fieldWeight in 1238, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1238)
      0.33333334 = coord(1/3)
    
    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.
  6. Leydesdorff, L.: Theories of citation? (1999) 0.02
    0.02158834 = product of:
      0.06476502 = sum of:
        0.06476502 = weight(_text_:reference in 5130) [ClassicSimilarity], result of:
          0.06476502 = score(doc=5130,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.31464687 = fieldWeight in 5130, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5130)
      0.33333334 = coord(1/3)
    
    Abstract
    Citations support the communication of specialist knowledge by allowing authors and readers to make specific selections in several contexts at the same time. In the interactions between the social network of authors and the network of their reflexive communications, a sub textual code of communication with a distributed character has emerged. Citation analysis reflects on citation practices. Reference lists are aggregated in scientometric analysis using one of the available contexts to reduce the complexity: geometrical representations of dynamic operations are reflected in corresponding theories of citation. The specific contexts represented in the modern citation can be deconstructed from the perspective of the cultural evolution of scientific communication
  7. Leydesdorff, L.: ¬The communication of meaning and the structuration of expectations : Giddens' "structuration theory" and Luhmann's "self-organization" (2010) 0.02
    0.018504292 = product of:
      0.055512875 = sum of:
        0.055512875 = weight(_text_:reference in 4004) [ClassicSimilarity], result of:
          0.055512875 = score(doc=4004,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 4004, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=4004)
      0.33333334 = coord(1/3)
    
    Abstract
    The communication of meaning as distinct from (Shannon-type) information is central to Luhmann's social systems theory and Giddens' structuration theory of action. These theories share an emphasis on reflexivity, but focus on meaning along a divide between interhuman communication and intentful action as two different systems of reference. Recombining these two theories into a theory about the structuration of expectations, interactions, organization, and self-organization of intentional communications can be simulated based on algorithms from the computation of anticipatory systems. The self-organizing and organizing layers remain rooted in the double contingency of the human encounter, which provides the variation. Organization and self-organization of communication are reflexive upon and therefore reconstructive of each other. Using mutual information in three dimensions, the imprint of meaning processing in the modeling system on the historical organization of uncertainty in the modeled system can be measured. This is shown empirically in the case of intellectual organization as "structurating" structure in the textual domain of scientific articles.
  8. Leydesdorff, L.; Bornmann, L.; Mutz, R.; Opthof, T.: Turning the tables on citation analysis one more time : principles for comparing sets of documents (2011) 0.02
    0.018504292 = product of:
      0.055512875 = sum of:
        0.055512875 = weight(_text_:reference in 4485) [ClassicSimilarity], result of:
          0.055512875 = score(doc=4485,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 4485, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=4485)
      0.33333334 = coord(1/3)
    
    Abstract
    We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks, the citation score of each paper is rated in terms of its percentile in the citation distribution. The percentile ranks approach allows for the formulation of a more abstract indicator scheme that can be used to organize and/or schematize different impact indicators according to three degrees of freedom: the selection of the reference sets, the evaluation criteria, and the choice of whether or not to define the publication sets as independent. Bibliometric data of seven principal investigators (PIs) of the Academic Medical Center of the University of Amsterdam are used as an exemplary dataset. We demonstrate that the proposed family indicators [R(6), R(100), R(6, k), R(100, k)] are an improvement on averages-based indicators because one can account for the shape of the distributions of citations over papers.
  9. Leydesdorff, L.; Radicchi, F.; Bornmann, L.; Castellano, C.; Nooy, W. de: Field-normalized impact factors (IFs) : a comparison of rescaling and fractionally counted IFs (2013) 0.02
    0.018504292 = product of:
      0.055512875 = sum of:
        0.055512875 = weight(_text_:reference in 1108) [ClassicSimilarity], result of:
          0.055512875 = score(doc=1108,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 1108, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=1108)
      0.33333334 = coord(1/3)
    
    Abstract
    Two methods for comparing impact factors and citation rates across fields of science are tested against each other using citations to the 3,705 journals in the Science Citation Index 2010 (CD-Rom version of SCI) and the 13 field categories used for the Science and Engineering Indicators of the U.S. National Science Board. We compare (a) normalization by counting citations in proportion to the length of the reference list (1/N of references) with (b) rescaling by dividing citation scores by the arithmetic mean of the citation rate of the cluster. Rescaling is analytical and therefore independent of the quality of the attribution to the sets, whereas fractional counting provides an empirical strategy for normalization among sets (by evaluating the between-group variance). By the fairness test of Radicchi and Castellano (), rescaling outperforms fractional counting of citations for reasons that we consider.
  10. Comins, J.A.; Leydesdorff, L.: Identification of long-term concept-symbols among citations : do common intellectual histories structure citation behavior? (2017) 0.02
    0.018504292 = product of:
      0.055512875 = sum of:
        0.055512875 = weight(_text_:reference in 3599) [ClassicSimilarity], result of:
          0.055512875 = score(doc=3599,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.2696973 = fieldWeight in 3599, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.046875 = fieldNorm(doc=3599)
      0.33333334 = coord(1/3)
    
    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.
  11. Leydesdorff, L.; Bihui, J.: Mapping the Chinese Science Citation Database in terms of aggregated journal-journal citation relations (2005) 0.02
    0.018269213 = product of:
      0.054807637 = sum of:
        0.054807637 = product of:
          0.109615274 = sum of:
            0.109615274 = weight(_text_:database in 4813) [ClassicSimilarity], result of:
              0.109615274 = score(doc=4813,freq=8.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.53595746 = fieldWeight in 4813, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4813)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    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.
  12. Zhou, P.; Leydesdorff, L.: ¬A comparison between the China Scientific and Technical Papers and Citations Database and the Science Citation Index in terms of journal hierarchies and interjournal citation relations (2007) 0.02
    0.018269213 = product of:
      0.054807637 = sum of:
        0.054807637 = product of:
          0.109615274 = sum of:
            0.109615274 = weight(_text_:database in 70) [ClassicSimilarity], result of:
              0.109615274 = score(doc=70,freq=8.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.53595746 = fieldWeight in 70, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=70)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Abstract
    The journal structure in the China Scientific and Technical Papers and Citations Database (CSTPCD) is analyzed from three perspectives: the database level, the specialty level, and the institutional level (i.e., university journals vs. journals issued by the Chinese Academy of Sciences). The results are compared with those for (Chinese) journals included in the Science Citation Index (SCI). The frequency of journal-journal citation relations in the CSTPCD is an order of magnitude lower than in the SCI. Chinese journals, especially high-quality journals, prefer to cite international journals rather than domestic ones; however, Chinese journals do not get an equivalent reception from their international counterparts. The international visibility of Chinese journals is low, but varies among fields of science. Journals of the Chinese Academy of Sciences have a better reception in the international scientific community than university journals.
    Object
    China Scientific and Technical Papers and Citations Database
  13. Leydesdorff, L.; Rotolo, D.; Rafols, I.: Bibliometric perspectives on medical innovation using the medical subject headings of PubMed (2012) 0.02
    0.018269213 = product of:
      0.054807637 = sum of:
        0.054807637 = product of:
          0.109615274 = sum of:
            0.109615274 = weight(_text_:database in 494) [ClassicSimilarity], result of:
              0.109615274 = score(doc=494,freq=8.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.53595746 = fieldWeight in 494, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=494)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    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.
  14. Leydesdorff, L.; Bornmann, L.: Integrated impact indicators compared with impact factors : an alternative research design with policy implications (2011) 0.02
    0.015420245 = product of:
      0.046260733 = sum of:
        0.046260733 = weight(_text_:reference in 4919) [ClassicSimilarity], result of:
          0.046260733 = score(doc=4919,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.22474778 = fieldWeight in 4919, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4919)
      0.33333334 = coord(1/3)
    
    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.
  15. Leydesdorff, L.; Hammarfelt, B.: ¬The structure of the Arts & Humanities Citation Index : a mapping on the basis of aggregated citations among 1,157 journals (2011) 0.02
    0.015420245 = product of:
      0.046260733 = sum of:
        0.046260733 = weight(_text_:reference in 4941) [ClassicSimilarity], result of:
          0.046260733 = score(doc=4941,freq=2.0), product of:
            0.205834 = queryWeight, product of:
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.050593734 = queryNorm
            0.22474778 = fieldWeight in 4941, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.0683694 = idf(docFreq=2055, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4941)
      0.33333334 = coord(1/3)
    
    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.
  16. Leydesdorff, L.; Moya-Anegón, F.de; Guerrero-Bote, V.P.: Journal maps on the basis of Scopus data : a comparison with the Journal Citation Reports of the ISI (2010) 0.01
    0.0131846685 = product of:
      0.039554004 = sum of:
        0.039554004 = product of:
          0.07910801 = sum of:
            0.07910801 = weight(_text_:database in 3335) [ClassicSimilarity], result of:
              0.07910801 = score(doc=3335,freq=6.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.38679397 = fieldWeight in 3335, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3335)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Abstract
    Using the Scopus dataset (1996-2007) a grand matrix of aggregated journal-journal citations was constructed. This matrix can be compared in terms of the network structures with the matrix contained in the Journal Citation Reports (JCR) of the Institute of Scientific Information (ISI). Because the Scopus database contains a larger number of journals and covers the humanities, one would expect richer maps. However, the matrix is in this case sparser than in the case of the ISI data. This is because of (a) the larger number of journals covered by Scopus and (b) the historical record of citations older than 10 years contained in the ISI database. When the data is highly structured, as in the case of large journals, the maps are comparable, although one may have to vary a threshold (because of the differences in densities). In the case of interdisciplinary journals and journals in the social sciences and humanities, the new database does not add a lot to what is possible with the ISI databases.
  17. Leydesdorff, L.: Can scientific journals be classified in terms of aggregated journal-journal citation relations using the Journal Citation Reports? (2006) 0.01
    0.012918284 = product of:
      0.03875485 = sum of:
        0.03875485 = product of:
          0.0775097 = sum of:
            0.0775097 = weight(_text_:database in 5046) [ClassicSimilarity], result of:
              0.0775097 = score(doc=5046,freq=4.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.37897915 = fieldWeight in 5046, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5046)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Abstract
    The aggregated citation relations among journals included in the Science Citation Index provide us with a huge matrix, which can be analyzed in various ways. By using principal component analysis or factor analysis, the factor scores can be employed as indicators of the position of the cited journals in the citing dimensions of the database. Unrotated factor scores are exact, and the extraction of principal components can be made stepwise because the principal components are independent. Rotation may be needed for the designation, but in the rotated solution a model is assumed. This assumption can be legitimated on pragmatic or theoretical grounds. Because the resulting outcomes remain sensitive to the assumptions in the model, an unambiguous classification is no longer possible in this case. However, the factor-analytic solutions allow us to test classifications against the structures contained in the database; in this article the process will be demonstrated for the delineation of a set of biochemistry journals.
  18. Leydesdorff, L.: Dynamic and evolutionary updates of classificatory schemes in scientific journal structures (2002) 0.01
    0.01065704 = product of:
      0.03197112 = sum of:
        0.03197112 = product of:
          0.06394224 = sum of:
            0.06394224 = weight(_text_:database in 1249) [ClassicSimilarity], result of:
              0.06394224 = score(doc=1249,freq=2.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.31264183 = fieldWeight in 1249, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1249)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    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.
  19. Leydesdorff, L.; Zhou, P.: Co-word analysis using the Chinese character set (2008) 0.01
    0.01065704 = product of:
      0.03197112 = sum of:
        0.03197112 = product of:
          0.06394224 = sum of:
            0.06394224 = weight(_text_:database in 1970) [ClassicSimilarity], result of:
              0.06394224 = score(doc=1970,freq=2.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.31264183 = fieldWeight in 1970, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1970)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Abstract
    Until recently, Chinese texts could not be studied using co-word analysis because the words are not separated by spaces in Chinese (and Japanese). A word can be composed of one or more characters. The online availability of programs that separate Chinese texts makes it possible to analyze them using semantic maps. Chinese characters contain not only information but also meaning. This may enhance the readability of semantic maps. In this study, we analyze 58 words which occur 10 or more times in the 1,652 journal titles of the China Scientific and Technical Papers and Citations Database. The word-occurrence matrix is visualized and factor-analyzed.
  20. Leydesdorff, L.; Salah, A.A.A.: Maps on the basis of the Arts & Humanities Citation Index : the journals Leonardo and Art Journal versus "digital humanities" as a topic (2010) 0.01
    0.009134606 = product of:
      0.027403818 = sum of:
        0.027403818 = product of:
          0.054807637 = sum of:
            0.054807637 = weight(_text_:database in 3436) [ClassicSimilarity], result of:
              0.054807637 = score(doc=3436,freq=2.0), product of:
                0.20452234 = queryWeight, product of:
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.050593734 = queryNorm
                0.26797873 = fieldWeight in 3436, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.042444 = idf(docFreq=2109, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3436)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    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.