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.

Growth in number of documents by week:

Date Number of documents in Scopus Number of documents in analysis
16th March 296 197
23rd March 411 280
30th March 828 502
6th April 1275 784
13th April 1660 1097
20th April 2281 1546
27th April 4578 2585
4th May 6135 3441
11th May 7328 4207
18th May 8209 5021
25th May 11380 6213
01st June 13226 7490
08th June 15178 8810
15th June 17204 10256
22nd June 18935 11329
29th June 21237 12373
06th July 23120 13614
13th July 25916 15409
20th July 27939 16935
27th July 30021 Not applicable
3rd August 32604 20329
10th August 34066 Not applicable
17th August 37113 23392
24th August 38223 Not applicable
31st August 41040 Not applicable
7th September 43197 Not applicable
14th September 45638 Not applicable
21st September 48734 Not applicable
28th September 51430 Not applicable
05th October 53738 Not applicable
12th October 55362 Not applicable
19th October 57733 Not applicable

 

Network Visualization of Bibliometric Coupling Analysis of recent COVID-19 Literature, based on the publications the past week

Network Visualization of Bibliometric Coupling Analysis of recent COVID-19 Literature as it looks like on September 28th, 2020

This week we analyze articles made available in the past week, with reference lists. There were 2696 new documents, of which 1647 include the necessary bibliographic information for a coupling analysis. For the analysis, we used linlog and total link strength. The minimum cluster size was set to 30. There are 7 main clusters in the map.

VOSViewer files:

To open the map directly in VOSviewer, please use these the latest MAP and NET files, available through the Open Science Foundation (OSF) repository:
https://osf.io/54gqw/

 

Network Visualization of Bibliometric Coupling Analysis of recent COVID-19 Literature, based on the publications the past week

Network Visualization of Bibliometric Coupling Analysis of recent COVID-19 Literature as it looks like on September 21st, 2020

This week we analyze articles made available in the past week, with reference lists. There were 3096 new documents, of which 1791 include the necessary bibliographic information for a coupling analysis. For the analysis, we used linlog and total link strength. The minimum cluster size was set to 15. There are 5 main clusters in the map.

VOSViewer files:

To open the map directly in VOSviewer, please use these the latest MAP and NET files, available through the Open Science Foundation (OSF) repository:
https://osf.io/54gqw/

 

Network Visualization of Bibliometric Coupling Analysis of recent COVID-19 Literature, based on the publications the past week

Network Visualization of Bibliometric Coupling Analysis of recent COVID-19 Literature as it looks like on September 14th, 2020

This week we analyze articles made available in the past week, with reference lists. There were 2441 new documents, of which 1317 include the necessary bibliographic information for a coupling analysis. For the analysis, we used linlog and total link strength. The minimum cluster size was set to 15. There are 8 main clusters in the map.

VOSViewer files:

To open the map directly in VOSviewer, please use these the latest MAP and NET files, available through the Open Science Foundation (OSF) repository:
https://osf.io/54gqw/