Abstract
Investigating the relationships found in the documentation of a subject field is one method of examining the communication taking place in that field. Bibliometrics provides an objective method for this type of investigation. Coauthorship, while intuitively seeming to indicate strong communication links, nevertheless has been shown to produce graphical structures that vary with changes in threshold. Having determined that clustering structure does exist in the data, preferred partitions are identified as those least likely to have occurred by chance. Further analysis is made to test that the preferred or “meaningful” structures produced from the coauthor relationship do indeed correspond with empirical evidence of “meaning”. A small dataset of 371 authors and 550 coauthor pairs is used to investigate correspondence between experimental structures and empirical evidence. Results show that components of the experimental structures are largely consistent with subject content groups as determined by index terms. Geographic focus accounts for about half the cases showing term overlap. Hence, we have some evidence that bibliometric structures determined from the coauthor relationship may be consistent with networks of communication. If this continues to be documented by further research, bibliometric analysis of coauthor relationships found in the scholarly communication of a subject area can become a basic tool for communication research.
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A. Pritchard, Statistical bibliography or bibliometrics?Journal of Documentation, 25 (1969) 348.
D. De Solla Price, D. de B. Beaver, Collaboration in an invisible college,American Psychologist, 21 (1966) 1011–1018.
S. Crawford, Informal communication among scientists in sleep research,Journal of the American Society for Information Science, 22 (1971) 301–310.
D. Crane,Invisible Colleges: Diffusion of Knowledge in Scientific Communities, Chicago, University of Chicago Press, 1972.
N. C. Mullins,Theories and Theory Groups in Contemporary American Sociology, New York, Harper and Row, 1973.
E. Garfield, Citation analysis as a tool in journal evaluation,Science, 178 (1972) 476.
H. Small, Co-citation in the scientific literature: A new measure of the relationship between two documents,American Documentation, 14 (1963) 10–25.
H. Small, B. C. Griffith, The structure of scientific literatures I, II,Science Studies, 4 (1974) 17–40.
M. M. Kessler, Bibliographic coupling between scientific papersAmerican Documentation, 14 (1963) 10–25.
H. D. White, B. C. Griffith, Author cocitation: A literature measure of intellectual structure,Journal of the American Society for Information Science, 32 (1981) 163–171.
W. M. Shaw, Jr, Information theory and scientific communication,Scietometrics, 3 (1981) 235–249.
E. L. Logan, W. M. Shaw, Jr, An Investigation of the co-author graph,Journal of the American Society for Information Science, 38 (1987) 262–268.
S. Crawford,op. cit. 2..
D. Crane,op. cit. 2..
E. L. Logan, W. M. Shaw, Jr., An Investigation of the co-author graph,Journal of the American Society for Inforamtion Science, 38 (1987) 262–268.
E. L. Logan, W. M. Shaw, Jr.. On the statistical validity of co-author partitions.Processing of the American Society for Information Science, 21 (1984) 208–211.
W. M. Shaw, Jr. Statistical disorder and the analysis of a communication graph,Journal of the american Society for Information Science, 34 (1983) 146–149.
F. Harary,Graph theory, Reading, Mass, Addison-Wesley; 1969.
R. Dubes, A. K. Jain, Clustering methodologies in exploratory data analysis, In:M. C. Yovits (Ed.) Advances in Computer, 19 (1950) 576–577.
R. F. Ling, G. G. Killough, Probability tables for cluster analysis based on a theory of random graphs,Journal of the American Statistical Association, 71 (1976) 293–300.
Literature of Leishmaniasis, Fileriasis, Trypansomiasis, Leprosy, Malaria, and Schistosomiasis found in theMedline database for the years 1977–1982.
Computer programsCoath andRangrf, written byW. M. Shaw Jr. now of the University of North Carolina at Chapel Hill were used for Leishmaniasis, Fileriasis, and Trypanosomiasis;Coa1, andCoardn, written by Kermit Rose of the Computing Center at Florida State University were used for Leprosy, Malaria, and Schistosomiasis.
E. L. Logan, W. M. Shaw, Jr. An Investigation of regularities in coauthor graphs,Proceedings of the American Society for Information Science, 25 (1988) 66–69.
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Logan, E.L., Shaw, W.M. A bibliometric analysis of collaboration in a medical specialty. Scientometrics 20, 417–426 (1991). https://doi.org/10.1007/BF02019762
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DOI: https://doi.org/10.1007/BF02019762