Analysis of coronavirus literature

These maps has been realized using Gargantext from a PubMed Corpora with query "coronavirus" on Feb 5 2020 (6560 documents from Jan 2000 to present). The methodology is described here

When you click on a term, the most related terms are displayed in a tag cloud on the right along with the Publications from PubMed that mention the most the selected terms (Jan. 2000 until March 26 2020).

In the Distributional maps (the first map to be loaded) links between terms capture a proximity measure that takes into account the profiles of interaction of each term with the others. It can infer relevant relations between terms even if their haven't co-occur in a paper (second order proximity measure).

In the Conditional map, links between terms represent the conditionnal probability of having one terms knowing the other in a paper (its the confidence measure).

In each graph, the node size is a fonction of the pagerank of the term in the graph.

The mathematical formula of these proximity measure can be found in the Gargantext documentation.

Download all the related data including the interactive explorer at https://doi.org/10.7910/DVN/QLQ0HB

Enjoy the exploration.