-
Leydesdorff, L.; Persson, O.: Mapping the geography of science : distribution patterns and networks of relations among cities and institutes (2010)
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- Abstract
- Using Google Earth, Google Maps, and/or network visualization programs such as Pajek, one can overlay the network of relations among addresses in scientific publications onto the geographic map. The authors discuss the pros and cons of various options, and provide software (freeware) for bridging existing gaps between the Science Citation Indices (Thomson Reuters) and Scopus (Elsevier), on the one hand, and these various visualization tools on the other. At the level of city names, the global map can be drawn reliably on the basis of the available address information. At the level of the names of organizations and institutes, there are problems of unification both in the ISI databases and with Scopus. Pajek enables a combination of visualization and statistical analysis, whereas the Google Maps and its derivatives provide superior tools on the Internet.
- Date
- 23. 7.2010 13:10:08
-
Leydesdorff, L.: Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports (2004)
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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.
-
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.; Bihui, J.: Mapping the Chinese Science Citation Database in terms of aggregated journal-journal citation relations (2005)
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- Date
- 8. 1.2006 18:53:23
-
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)
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- Date
- 3. 3.2007 18:23:57
-
Leydesdorff, L.: How are new citation-based journal indicators adding to the bibliometric toolbox? (2009)
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- Date
- 19. 7.2009 12:23:20
-
Leydesdorff, L.; Rafols, I.: ¬A global map of science based on the ISI subject categories (2009)
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- Date
- 23. 2.2009 19:54:19
-
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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- Date
- 31. 5.2010 15:02:23
-
Bauer, J.; Leydesdorff, L.; Bornmann, L.: Highly cited papers in Library and Information Science (LIS) : authors, institutions, and network structures (2016)
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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.
-
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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- 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
-
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
-
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.
-
Lucio-Arias, D.; Leydesdorff, L.: ¬An indicator of research front activity : measuring intellectual organization as uncertainty reduction in document sets (2009)
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- Date
- 2. 2.2010 19:29:29
-
Leydesdorff, L.; Zhou, P.: Co-word analysis using the Chinese character set (2008)
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- Date
- 12. 7.2008 18:46:29
-
Chen, C.; Leydesdorff, L.: Patterns of connections and movements in dual-map overlays : a new method of publication portfolio analysis (2014)
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- Date
- 29. 1.2014 16:38:28
-
Leydesdorff, L.; Ivanova, I.A.: Mutual redundancies in interhuman communication systems : steps toward a calculus of processing meaning (2014)
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- Date
- 29. 1.2014 16:44:54
-
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
