Cited References and Medical Subject Headings (MeSH) as Two Different Knowledge Representations: Clustering and Mappings at the Paper Level

TL;DR

This paper develops methods to integrate MeSH terms with citation data, enabling new analyses of scientific knowledge structures and research front variations in biomedical literature.

Contribution

It introduces routines to merge MeSH terms with citation matrices, facilitating advanced science indicator studies and normalization techniques.

Findings

MeSH terms reflect research front variation and novelty.

Referenced journals provide archival structure.

Citing/cited matrices can be used for main-path analysis.

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 (AD). 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.