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Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level

Author

Listed:
  • Loet Leydesdorff

    (University of Amsterdam)

  • Jordan A. Comins

    (Virginia Tech Applied Research Corporation)

  • Aaron A. Sorensen

    (Digital Science, Inc.)

  • Lutz Bornmann

    (Administrative Headquarters of the Max Planck Society)

  • Iina Hellsten

    (University of Amsterdam)

Abstract

For the biomedical sciences, the Medical Subject Headings (MeSH) make available a rich feature which cannot currently be merged properly with widely used citing/cited data. Here, we provide methods and routines that make MeSH terms amenable to broader usage in the study of science indicators: using Web-of-Science (WoS) data, one can generate the matrix of citing versus cited documents; using PubMed/MEDLINE data, a matrix of the citing documents versus MeSH terms can be generated analogously. The two matrices can also be reorganized into a 2-mode matrix of MeSH terms versus cited references. Using the abbreviated journal names in the references, one can, for example, address the question whether MeSH terms can be used as an alternative to WoS Subject Categories for the purpose of normalizing citation data. We explore the applicability of the routines in the case of a research program about the amyloid cascade hypothesis in Alzheimer’s disease. One conclusion is that referenced journals provide archival structures, whereas MeSH terms indicate mainly variation (including novelty) at the research front. Furthermore, we explore the option of using the citing/cited matrix for main-path analysis as a by-product of the software.

Suggested Citation

  • Loet Leydesdorff & Jordan A. Comins & Aaron A. Sorensen & Lutz Bornmann & Iina Hellsten, 2016. "Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2077-2091, December.
  • Handle: RePEc:spr:scient:v:109:y:2016:i:3:d:10.1007_s11192-016-2119-7
    DOI: 10.1007/s11192-016-2119-7
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    References listed on IDEAS

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    1. Bornmann, Lutz & Marx, Werner & Schier, Hermann & Rahm, Erhard & Thor, Andreas & Daniel, Hans-Dieter, 2009. "Convergent validity of bibliometric Google Scholar data in the field of chemistry—Citation counts for papers that were accepted by Angewandte Chemie International Edition or rejected but published els," Journal of Informetrics, Elsevier, vol. 3(1), pages 27-35.
    2. Petersen, Alexander M. & Rotolo, Daniele & Leydesdorff, Loet, 2016. "A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings," Research Policy, Elsevier, vol. 45(3), pages 666-681.
    3. Daniele Rotolo & Ismael Rafols & Michael M. Hopkins & Loet Leydesdorff, 2017. "Strategic intelligence on emerging technologies: Scientometric overlay mapping," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(1), pages 214-233, January.
    4. John S. Liu & Louis Y.Y. Lu, 2012. "An integrated approach for main path analysis: Development of the Hirsch index as an example," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(3), pages 528-542, March.
    5. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    6. Loet Leydesdorff & Daniele Rotolo & Ismael Rafols, 2012. "Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2239-2253, November.
    7. Diana Hicks & Jian Wang, 2011. "Coverage and overlap of the new social sciences and humanities journal lists," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 284-294, February.
    8. Daniele Rotolo & Loet Leydesdorff, 2015. "Matching Medline/PubMed data with Web of Science: A routine in R language," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(10), pages 2155-2159, October.
    9. Kevin J. Boudreau & Eva C. Guinan & Karim R. Lakhani & Christoph Riedl, 2016. "Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance, Novelty, and Resource Allocation in Science," Management Science, INFORMS, vol. 62(10), pages 2765-2783, October.
    10. Thor, Andreas & Marx, Werner & Leydesdorff, Loet & Bornmann, Lutz, 2016. "Introducing CitedReferencesExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardization," Journal of Informetrics, Elsevier, vol. 10(2), pages 503-515.
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    3. Hwang, Seonho & Shin, Juneseuk, 2019. "Extending technological trajectories to latest technological changes by overcoming time lags," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 142-153.

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