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

Loet Leydesdorff, Jordan A. Comins (), Aaron A. Sorensen (), Lutz Bornmann () and Iina Hellsten ()
Additional contact information
Jordan A. Comins: Virginia Tech Applied Research Corporation
Aaron A. Sorensen: Digital Science, Inc.
Iina Hellsten: University of Amsterdam

Scientometrics, 2016, vol. 109, issue 3, No 35, 2077-2091

Abstract: 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.

Keywords: MeSH; Citation; Journal; Main path; Alzheimer (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11192-016-2119-7

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