, Volume 33, Issue 2, pp 257–262 | Cite as

The use of citations matrices to group journals

  • M. P. Burton
Short Communication


A method of grouping journals within a wide discipline area into clusters is proposed, based on a algorithm that attempts to re-order a citations matrix so that it is block diagonal, or block recursive. The algorithm is based on a penalty function which allows one to account for the level of citation, not just the distribution of citations between journals. A case study involving eight economics journals is presented which illustrates the principles involved, but which also highlights the computational problems associated with extending the analysis to larger numbers of journals.


Penalty Function Economics Journal Computational Problem Discipline Area Group Journal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    P. Doreian, A revised measure of standing of journals in stratified networks,Scientometrics, 11 (1987) 71–80.Google Scholar
  2. 2.
    R. Todorov, W. Glänzel, Journal citation measures: a concise review,Journal of Information Science, 4 (1988) 47–56.Google Scholar
  3. 3.
    H. Small, A Sci-map case study: Building a map of AIDS research,Scientometrics, 30, (1994) 229–241.Google Scholar
  4. 4.
    J. T. Sharabchiev, Cluster analysis of bibliographic references as a scientometric method,Scientometrics, 15 (1989) 127–137.Google Scholar
  5. 5.
    M. P. Carpenter, F. Narin, Clustering of Scientific Journals,Journal of the American Society of Information Science, 24 (1973) 425–436.Google Scholar
  6. 6.
    R. Tijssen, J. de Leeuw, A. F. J. Van Raan, Quasi-correspondence analysis of square scientometric transaction matrices,Scientometrics, 11 (1987) 347–361.Google Scholar
  7. 7.
    R. S. Burt,Towards a Structural Theory of Action, Academic Press, New York, 1982.Google Scholar
  8. 8.
    E. Garfield,Social Science Citation Index Journal Citation Reports, ISI Philadelphia, 1992.Google Scholar
  9. 9.
    D. E. Goldberg,Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading, Massachusetts, 1989.Google Scholar

Copyright information

© Akadémiai Kiadó 1995

Authors and Affiliations

  • M. P. Burton
    • 1
  1. 1.School of Economic StudiesUniversity ManchesterManchesterUK

Personalised recommendations