Bibliometric Coupling Analysis of COVID-19 Literature

A Bibliographic coupling analysis examines the reference lists of documents, to identify where articles share a common reference. The degree of overlap between article’s reference list represents the strength of the connection between them. Greater overlap means two documents share a large proportion of references, and thus a probability that the content are on related topics. Conversely, little overlap indicates the documents are based on distinct pieces of literature, with few commonalities.

For more information about what a bibliometric coupling analysis is, please see the about page.

Applications for the bibliometric coupling results:

• Organizes published articles by topics, enables the reader to identify articles within an area of interest.
• It is a complementary way to identify related research. The results are not based on search terms, so identifying related articles through this method opens the possibility to make valuable and novel connections between research articles.

To access the interactive map, you need to open the graph in VosViewer, which allows you to search the map, see article information on each node in the graph diagram, and by clicking on the node, open the article in a browser window. To open the map in VOSviewer, please download the free program: VOSviewer here, and open the files.

Insights and trends

When we initiated this project in mid-March 2020, there were 296 documents on COVID-19 in Scopus, of which 197 included the bibliometric information necessary to conduct a coupling analysis. Since then, there has been a sharp increase, and in mid-September, 45638 documents on the pandemic was available in the database.

Coupling analyses on documents from early in the pandemic suggested four topics: 1) The contributions were on “Overview of the new virus”, 2) “Clinical medicine,”, 3) “On the virus,” which included topics ranging from the origin of the virus, its genome, possible therapeutics and early research on these topics, and 4) literature on “Reproduction rate and spread.”  For a more detailed description, please see our preprint

In July, we conducted a coupling analysis on journals, creating a network graph showing journals that have published ten or more articles on COVID-19 since March. Of the (then) 4585 journals that had published COVID-19 literature, 706 have published ten or more articles. The analyses showed 5 clusters. In the different clusters, these were the journals with the highest closeness centrality: 1) Diabetes And Metabolic Syndrome: Clinical Research And Reviews, BMJ, and Diabetes Research And Clinical Practice. 2) Science Of The Total Environment, International Journal Of Infectious Diseases, and Lancet. 3) Journal Of Medical Virology, Frontiers In Public Health, and Medical Hypotheses. 4) International Journal Of Environmental Research And Public Health, Sustainability, Brain, Behavior, And Immunity. 5) Jama – Journal Of The American Medical Association, Pediatric Pulmonology, and Frontiers In Pediatrics. For more details, see this post.