Mapping the biomedical sciences using Medical Subject Headings: a comparison between MeSH co-assignments and MeSH citation pairs

• Published in: Journal of the Medical Library Association Vol. 109; no. 3; pp. 441 - 449
• Main Authors: Shu, Fei, Qiu, Junping, Larivière, Vincent
• Format: Journal Article
• Language: English
• Published: United States Medical Library Association 01.07.2021; University Library System, University of Pittsburgh
• Subjects: Analysis; Arthropods; citation; Citation analysis; Classification; co-assignment; Cocitation; gephi; Invertebrates; Libraries; Library of Congress Subject Headings; Literary research; map of life sciences; Mapping; Medical informatics; Medical journals; Medical sciences; Medical Subject Headings; Medical Subject Headings-MeSH; MEDLINE; mesh; Original Investigation; Software; Subject heading schemes; United States; MeSH; map of life sciences; Gephi; citation; co-assignment
• ISSN: 1536-5050; 1558-9439
• DOI: 10.5195/jmla.2021.1173

This study compares two maps of biomedical sciences using Medical Subject Headings (MeSH) term co-assignments versus MeSH terms of citing/cited articles and reveals similarities and differences between the two approaches. MeSH terms assigned to 397,475 journal articles published in 2015, as well as their 4,632,992 cited references, were retrieved from Web of Science and MEDLINE databases, respectively, which formed over 7 million MeSH co-assignments and nearly 18 million direct citation pairs. We generated six network visualizations of biomedical science at three levels using Gephi software based on these MeSH co-assignments and citation pairs. The MeSH co-assignment map contained more nodes and edges, as MeSH co-assignments cover all medical topics discussed in articles. By contrast, the MeSH citation map contained fewer but larger nodes and wider edges, as citation links indicate connections to two similar medical topics. These two types of maps emphasize different aspects of biomedical sciences, with MeSH co-assignment maps focusing on the relationship between topics in different categories and MeSH direct citation maps providing insights into relationships between topics in the same or similar category.