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Representing a scientific field: A bibliometric approach

Abstract

A new bibliometric method is proposed for representing links between subfields as defined by a classification scheme. The frequency of co-occurrence of articles from different subfields in selected journals is used for measuring the degree of relatedness between these subfields. The results of such quantitative analysis could be compared to the tree topology of the classification network established in a qualitative analysis. The method is applied to describe the internal links within the field of condensed matter physics using the 1984 Physics Abstracts database. A distinction is made between experimental and theoretical links on the basis of treatment codes assigned to journal articles. The links described by cluster analysis are matched against the cross-reference network of the International Classification for Physics.

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References

  1. H. SMALL, Co-citation in the scientific literature: A new measure of relationship between two documents,Journal of the American Society for Information Science, 24 (1973) 265–269.

    Google Scholar 

  2. D. SULLIVAN, D. H. WHITE, E. BARBONI, Co-citation analysis of science: An evaluation,Social Studies of Science, 7 (1977) 223–240.

    Google Scholar 

  3. H. G. SMALL, B. C. GRIFFITH, The structure of scientific literatures 1: Identifying and graphing specialties,Science Studies, 4 (1974) 17–40.

    Google Scholar 

  4. E. NOMA, Co-citation analysis and the invisible college,Journal of the American Society for Information Science, 35 (1984) 29–33.

    Google Scholar 

  5. A. PICKERING, E. NADEL, Charm revisited: A quantitative analysis of the HEP literature,Social Studies of Science, 17 (1987) 87–113.

    Google Scholar 

  6. D. HICKS, Limitations of co-citation analysis as a tool for science policy,Social Studies of Science, 17 (1987) 295–316.

    Google Scholar 

  7. H. SMALL, E. SWEENEY, Clustering the Science Citation Index using co-citations I. Comparison of methods,Scientometrics, 7 (1985) 391–409.

    Google Scholar 

  8. W. M. SHAW, Jr., Critical thresholds in co-citation graphs.Journal of the American Society for Information Science, 36 (1985) 38–43.

    Google Scholar 

  9. H. SMALL, E. GARFIELD, The geography of science: Disciplinary and national mappings,Journal of Information Science, 11 (1985) 147–159.

    Google Scholar 

  10. A. RIP, J.-P. COURTIAL, Co-word maps of biotechnology: An example of cognitive scientometrics,Scientometrics, 6 (1984) 381–400.

    Google Scholar 

  11. M. CALLON, J. LAW, A. RIP (Eds),Mapping the Dynamics of Science and Technology, London, Macmillan, 1986.

    Google Scholar 

  12. L. LEYDESDORFF, Various methods for the mapping of science,Scientometrics, 11 (1987) 295–324.

    Google Scholar 

  13. H. SMALL, E. SWEENEY, E. GREENLEE, Clustering the Science Citation Index using co-citations II. Mapping science,Scientometrics, 8 (1985) 321–340.

    Google Scholar 

  14. H. SMALL, E. GARFIELD, op. cit., Ref. 9..

    Google Scholar 

  15. R. J. W. TIJSSEN, J. De LEEUW, A. F. J. Van RAAN, Exploring Quantitative Relations within a Set of Scientific Entitites. First International Conference on Bibliometrics, August 24–28, 1987, Diepenbeek, Belgium.

  16. A. D. PRATT, A measure of class concentration in bibliometrics,Journal of the American Society for Information Science, 28 (1977) 285–292.

    Google Scholar 

  17. A. SCHUBERT, W. GLAENZEL, Statistical reliability of comparisons based on the citation impact of scientific publications,Scientometrics, 5 (1983) 59–74.

    Google Scholar 

  18. J. HARTIGAN, Cluster analysis of variables, in: W. J. DIXON, M. B. BROWN (Eds),Biomedical Computer Programs, P-Series 1979, Univ. California Press, Los Angeles, CA, 1979, 623–632.

    Google Scholar 

  19. A. BERTHELOT, P. CLAGUE, S. SCHIMINOVICH, W. ZWIRNER, The ICSU AB International Classification System for physics: Its history and future,Journal of the American Society for Information Science, 30 (1979) 343–352

    Google Scholar 

  20. H. SMALL, E. GARFIELD, Op. cit., Ref. 9, p. 150.

    Google Scholar 

  21. H. SMALL, E. SWEENEY, E. GREENLEE, Op. cit., Ref. 13,, p. 335.

    Google Scholar 

  22. D. HICKS, Op. cit., Ref. 6,, p. 296.

    Google Scholar 

  23. H. SMALL, E. GARFIELD, Op. cit., Ref. 9, p. 159.

    Google Scholar 

  24. A. D. PRATT, Op. cit., Ref. 16,.

    Google Scholar 

  25. J. HARTIGAN, Op. cit., Ref. 18,.

    Google Scholar 

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Todorov, R. Representing a scientific field: A bibliometric approach. Scientometrics 15, 593–605 (1989). https://doi.org/10.1007/BF02017072

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  • DOI: https://doi.org/10.1007/BF02017072

Keywords

  • Qualitative Analysis
  • Quantitative Analysis
  • Cluster Analysis
  • Classification Scheme
  • International Classification