For text-based clustering, two methods were used: topic modeling and k-means using SPECTER embedding, which is a new method to generate document-level embedding of scientific documents. 

COVID-19 research in Wikipedia methodology: text-based clustering

For citation network clustering, researchers created a bibliographic couplic citation network using publications and references from Dimensions. Edges were then weighted through fractional counting and then clustered through the Leiden algorithm. Through this, they found that the largest 43 clusters accounted for half the nodes in their network. The largest cluster had 15,749 nodes. 

COVID-19 research in Wikipedia methodology: citation-network clustering

Researchers used clutering analysis using publication text and citation data. For publication text, they used text-based clustering. For citation data, they did citation-network clustering. 

University of California, Berkeley

COVID-19 research in Wikipedia methodology

Colavizza, G. (2020). COVID-19 research in Wikipedia. Quantitative Science Studies, 1-32. https://www.mitpressjournals.org/doi/full/10.1162/qss_a_00080 

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