Advertisement

Scientometrics

, Volume 41, Issue 3, pp 389–410 | Cite as

Neural networks research in context: A longitudinal journal cocitation analysis of an emerging interdisciplinary field

  • Katherine W. McCain
Article

Abstract

A cocitation analysis for thirty-six journals and other publications in neural networks research and related disciplines was conducted over three consecutive time periods spanning the years 1990-early 1997. Cluster analysis and MDS maps identified groupings representing foundation research areas (physics/optics, computer engineering, neuroscience, expert systems & cognition, and perception) along with neural networks and mathematical modeling of neural systems. Principal components analysis demonstrated a similar structure, with several journals and books loading on a majority of the factors. An INDSCAL analysis showed an increasing separation between natural sciences/psychology and engineering/neural networks research from the first time period to the third.

Keywords

Neural Network Neural System Mathematical Bioscience Consecutive Time Period Cocitation Analysis 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes and references

  1. 1.
    Van Raan, A. F. J.;Tijssen, R. J. W. 1993. The neural net of neural networks research: An exercise in bibliometric mapping,Scientometrics, 26: 169–192.CrossRefGoogle Scholar
  2. 2.
    Rappa, M. A.;Debakere, K. 1989. The Emergence of a New Technology: The Case of Neural Networks. WP#3031-89-BPS., Cambridge, MA: Sloan School of Management, Massachusetts Institute of Technology.Google Scholar
  3. 3.
    Rappa, M. A.;Debakere, K. 1990. International Survey of the Neural Network Research Community: Preliminary Report. WP#3170-90-BPS., Cambridge, MA: Sloan School of Management, Massachusetts Institute of Technology.Google Scholar
  4. 4.
    Cowan, J. D. 1990. Neural networks: The early days. In:Advances in Neural Information Processing Systems 2.,D. S. Touretzky (Ed.), San Mateo, CA: Morgan Kauffman. p. 828–842.Google Scholar
  5. 5.
    Hecht-Nielsen, R. 1990.Neurocomputing, Reading, MA: Addison-Wesley Publishing Co. See especially p. 14–19.Google Scholar
  6. 6.
    Simpson, P. K., 1990.Artificial Neural Systems: Foundations, Paradigms, Applications, and Implementations, New York, NY: Pergamon Press.Google Scholar
  7. 7.
    Allman, W. F. 1989.Apprentices of Wonder, New York, NY: Bantam Books.Google Scholar
  8. 8.
    Coveney, P.;Highfield, R. 1995.The Frontiers of Complexity, New York, NY: Fawcett Columbine.Google Scholar
  9. 9.
    Anderson, J. A.;Rosenfeld, E. 1988.Neurocomputing: Foundations of Research, Cambridge, MA: MIT Press.Google Scholar
  10. 10.
    Anderson, J. A.;Pellionisz, A.;Rosenfeld, E. 1990.Neurocomputing 2: Directions for Research Cambridge, MA: MIT Press.Google Scholar
  11. 11.
    McCain, K. W.;Whitney, J. P. 1994. Contrasting assessments of interdisciplinarity in emerging specialties: The case of neural netowrks research,Knowledge: Creation, Diffusion, Utilization, 15(3): 285–306.Google Scholar
  12. 12.
    Tijssen, R. J. W. 1993. A scientometric cognitive study of neural network research: Expert mental maps versus bibliometric maps,Scientometrics, 28:111–136.CrossRefGoogle Scholar
  13. 13.
    Van Den Besselaar, P.;Leydesdorff, L. 1996. Mapping change in scientific specialties: A scientometric reconstruction of the development of artificial intelligence,Journal of the American Society for Information Science, 47(6): 415–436.CrossRefGoogle Scholar
  14. 14.
    The fifth,International Journal of Neural Networks, has ceased publication.Google Scholar
  15. 15.
    Kohonen, T. 1989.Self-Organization and Associative Memory, New York, NY: Springer-Verlag.Google Scholar
  16. 16.
    Rumelhart, D. E.;McClelland, J. L. (Eds), 1986.Parallel Distributed Processing: Explorations in the Microstructure of Cognition, 2v, Cambridge, MA: MIT Press.Google Scholar
  17. 17.
    Hebb, D. O. 1949.The Organization of Behavior, New York, NY: John Wiley.Google Scholar
  18. 18.
    McCain, K. W. 1991. Mapping economics through the journal literature: An experiment in journal cocitation analysis,Journal of the American Society for Information Science, 42(4): 290–296.CrossRefGoogle Scholar
  19. 20.
    McCain, K. W. 1990. Mapping authors in intellectual space: A technical overview,Journal of the American Society for Information Science, 41(6): 433–443.CrossRefGoogle Scholar
  20. 22.
    One is reminded of the three “point-of-interest” models in the VIBE system that visualizes the distribution of documents as they relate to two or more specific topics. Both interactive and static literature visualization techniques, including bibliometric mapping, are discussed inWhite, H. D.;McCain, K. W. 1997. Visualization of literatures,Annual Review of Information Science & Technology, 32: 3–72; the VIBE system is explained clearly inOlsen, K. A.; Korfhage, R. R.; Sochats, K. M.; Spring, M. B.; Williams, J. G. 1993. Visualization of a document collection: The VIBE system,Information Processing & Management, 29(1): 69–81.Google Scholar
  21. 23.
    Rikken, F.;Kiers, H. A. L.;Vos, R. 1995. Mapping the dynamics of adverse drug-reactions in subsequent time periods using INDSCAL,Scientometrics, 33: 367–380.CrossRefGoogle Scholar
  22. 24.
    White, H. D.; McCain, K. W. 1997. Visualizing a discipline: An author cocitation analysis of information science, 1972–1995,Journal of the American Society for Information Science (in press).Google Scholar
  23. 25.
    Coxon, A. P. M. 1982.The User's Guide to Multidimensional Scaling, Exeter, NH: Heinemann Educational Books Inc.Google Scholar
  24. 26.
    McCain, K. W. 1998. The Research Front Cluster History of Neural Networks Research, 1984–1991. in preparation.Google Scholar

Copyright information

© Akadémiai Kiadó 1998

Authors and Affiliations

  • Katherine W. McCain
    • 1
  1. 1.College of Information Science & TechnologyDrexel UniversityPhiladelphia(USA)

Personalised recommendations