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.

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

 

Network Visualization of Bibliometric Coupling Analysis of COVID-19 Literature as of July 6th, 2020

by | Jul 7, 2020 |

Network Visualization of Bibliometric Coupling Analysis of COVID-19 Literature as it looks like at July 6th, 2020

Corpus: 23120 documents, downloaded from Scopus. 13614 of these included reference lists and were included in the analysis. For the analysis, we used linlog and total link strength. The minimum cluster size was set to 15. There are 7 main clusters in the map.

There

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 COVID-19 Literature as of June 29th, 2020

by | Jun 30, 2020 |

Network Visualization of Bibliometric Coupling Analysis of COVID-19 Literature as it looks like at June 29th, 2020

Corpus: 21237 documents, downloaded from Scopus. 12373 of these included reference lists and were included in the analysis. For the analysis, we used linlog and total link strength. The minimum cluster size was set to 15. 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 COVID-19 Literature as of June 22nd, 2020

by | Jun 27, 2020 |

Network Visualization of Bibliometric Coupling Analysis of COVID-19 Literature as it looks like at June 22nd, 2020

Corpus: 18935 documents, downloaded from Scopus. 10256 of these included reference lists and were included in the analysis. For the analysis, we used linlog and total link strength. The minimum cluster size was set to 15.

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/