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. 

COVID-19 research in Wikipedia methodology: clusters

University of California, Berkeley

This paper looked at the information in Wikipedia related to COVID-19 by looking at the citations in Wikipedia. They found that new information about COVID-19 is being added to Wikipedia quickly and that editors tend to use literature that is highly cited and shared. 

COVID-19 research in Wikipedia

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

For published research related to COVID-19, looked at two lists of publications: the "Dimensions COVID-19 Publications" list and the "COVID-19 Open Research Dataset "(CORD-19). These lists are regularly updated. The date this study used for the cutoff for these lists is July 1, 2020. They merged the two lists and then removed the duplicates. 

For information in Wikipedia, data from Almetric, which provides Wikipedia citation data, was used. They needed up with a final set of 94,600 COVID-19 related publications. 

They also used data from Dimensions to get citation counts for COVID-19 related publications. 

COVID-19 research in Wikipedia data collection

- comparing Wikipedia coverage of COVID-19 with COVID-19 review articles
- studying the Wikipedia edit and discussion history
- studying editor motivations
- look at other sources of information that is cited by Wikipedia about COVID-19 as this study only looked at research articles
- look at how engagement on Wikipedia affects cited COVID-19 related sources


COVID-19 research in Wikipedia further work

- about two percent of COVID-19 related research articles is cited on Wikipedia
- tend to cite highly cited journals and reputable journals


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