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Automatic Term Identification for Bibliometric Mapping

Author

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  • van Eck, N.J.P.
  • Waltman, L.
  • Noyons, E.C.M.
  • Buter, R.K.

Abstract

A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

Suggested Citation

  • van Eck, N.J.P. & Waltman, L. & Noyons, E.C.M. & Buter, R.K., 2008. "Automatic Term Identification for Bibliometric Mapping," ERIM Report Series Research in Management ERS-2008-081-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:14056
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    References listed on IDEAS

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    1. E. C. M. Noyons & A. F. J. van Raan, 1998. "Monitoring scientific developments from a dynamic perspective: Self‐organized structuring to map neural network research," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(1), pages 68-81.
    2. Jesper W. Schneider, 2006. "Concept symbols revisited: Naming clusters by parsing and filtering of noun phrases from citation contexts of concept symbols," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 573-593, September.
    3. Alexander Kopcsa & Edgar Schiebel, 1998. "Science and technology mapping: A new iteration model for representing multidimensional relationships," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(1), pages 7-17.
    4. Hajime Eto, 2000. "Authorship and Citation Patterns in Operational Research Journals in Relation to Competition and Reform," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(1), pages 25-42, January.
    5. van Eck, N.J.P. & Waltman, L., 2006. "VOS: A New Method for Visualizing Similarities between Objects," ERIM Report Series Research in Management ERS-2006-020-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Hajime Eto, 2002. "Authorship and citation patterns in Management Science in comparison with operational research," Scientometrics, Springer;Akadémiai Kiadó, vol. 53(3), pages 337-349, March.
    7. Abraham Bookstein & Don R. Swanson, 1974. "Probabilistic models for automatic indexing," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 25(5), pages 312-316, September.
    8. Peters, H. P. F. & van Raan, A. F. J., 1993. "Co-word-based science maps of chemical engineering. Part I: Representations by direct multidimensional scaling," Research Policy, Elsevier, vol. 22(1), pages 23-45, February.
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    Citations

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    Cited by:

    1. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    2. Nees Jan Eck & Ludo Waltman & Ed C. M. Noyons & Reindert K. Buter, 2010. "Automatic term identification for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 581-596, March.

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    More about this item

    Keywords

    automatic term identification; bibliometric mapping; operations research; probabilistic latent semantic analysis; term map;
    All these keywords.

    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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