-
Bornmann, L.; Wagner, C.; Leydesdorff, L.: BRICS countries and scientific excellence : a bibliometric analysis of most frequently cited papers (2015)
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- Abstract
- The BRICS countries (Brazil, Russia, India, China, and South Africa) are notable for their increasing participation in science and technology. The governments of these countries have been boosting their investments in research and development to become part of the group of nations doing research at a world-class level. This study investigates the development of the BRICS countries in the domain of top-cited papers (top 10% and 1% most frequently cited papers) between 1990 and 2010. To assess the extent to which these countries have become important players at the top level, we compare the BRICS countries with the top-performing countries worldwide. As the analyses of the (annual) growth rates show, with the exception of Russia, the BRICS countries have increased their output in terms of most frequently cited papers at a higher rate than the top-cited countries worldwide. By way of additional analysis, we generate coauthorship networks among authors of highly cited papers for 4 time points to view changes in BRICS participation (1995, 2000, 2005, and 2010). Here, the results show that all BRICS countries succeeded in becoming part of this network, whereby the Chinese collaboration activities focus on the US.
-
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)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.4, S.787-801
- Year
- 2010
-
Zhou, P.; Su, X.; Leydesdorff, L.: ¬A comparative study on communication structures of Chinese journals in the social sciences (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1360-1376
- Year
- 2010
-
Leydesdorff, L.; Persson, O.: Mapping the geography of science : distribution patterns and networks of relations among cities and institutes (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1622-1634
- Year
- 2010
-
Rafols, I.; Porter, A.L.; Leydesdorff, L.: Science overlay maps : a new tool for research policy and library management (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.9, S.1871-1887
- Year
- 2010
-
Leydesdorff, L.: ¬The communication of meaning and the structuration of expectations : Giddens' "structuration theory" and Luhmann's "self-organization" (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.2138-2150
- Year
- 2010
-
Leydesdorff, L.; Opthof, T.: Scopus's source normalized impact per paper (SNIP) versus a journal impact factor based on fractional counting of citations (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.11, S.2365-2369
- Year
- 2010
-
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)
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- Journal of the American Society for Information Science and Technology. 61(2010) no.2, S.352-369
- Year
- 2010
-
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)
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- 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.
-
Leydesdorff, L.; Zhou, P.; Bornmann, L.: How can journal impact factors be normalized across fields of science? : An assessment in terms of percentile ranks and fractional counts (2013)
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- Abstract
- Using the CD-ROM version of the Science Citation Index 2010 (N = 3,705 journals), we study the (combined) effects of (a) fractional counting on the impact factor (IF) and (b) transformation of the skewed citation distributions into a distribution of 100 percentiles and six percentile rank classes (top-1%, top-5%, etc.). Do these approaches lead to field-normalized impact measures for journals? In addition to the 2-year IF (IF2), we consider the 5-year IF (IF5), the respective numerators of these IFs, and the number of Total Cites, counted both as integers and fractionally. These various indicators are tested against the hypothesis that the classification of journals into 11 broad fields by PatentBoard/NSF (National Science Foundation) provides statistically significant between-field effects. Using fractional counting the between-field variance is reduced by 91.7% in the case of IF5, and by 79.2% in the case of IF2. However, the differences in citation counts are not significantly affected by fractional counting. These results accord with previous studies, but the longer citation window of a fractionally counted IF5 can lead to significant improvement in the normalization across fields.
-
Leydesdorff, L.; Vaughan, L.: Co-occurrence matrices and their applications in information science : extending ACA to the Web environment (2006)
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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.
-
Leydesdorff, L.; Ivanova, I.: ¬The measurement of "interdisciplinarity" and "synergy" in scientific and extra-scientific collaborations (2021)
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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.
-
Leydesdorff, L.: ¬The construction and globalization of the knowledge base in inter-human communication systems (2003)
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- Date
- 22. 5.2003 19:48:04
-
Leydesdorff, L.: Can networks of journal-journal citations be used as indicators of change in the social sciences? (2003)
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- Date
- 6.11.2005 19:02:22
-
Leydesdorff, L.; Sun, Y.: National and international dimensions of the Triple Helix in Japan : university-industry-government versus international coauthorship relations (2009)
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- Date
- 22. 3.2009 19:07:20
-
Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019)
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- Date
- 8. 1.2019 18:22:45
-
Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011)
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- Date
- 22. 1.2011 12:51:07
-
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)
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- Date
- 24. 8.2016 17:53:22
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Leydesdorff, L.; Johnson, M.W.; Ivanova, I.: Toward a calculus of redundancy : signification, codification, and anticipation in cultural evolution (2018)
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- Date
- 29. 9.2018 11:22:09
