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COVID-19 research in Wikipedia

Authors: Colavizza, Giovanni;

COVID-19 research in Wikipedia

Abstract

Wikipedia is one of the main sources of free knowledge on the Web. During the first few months of the pandemic, over 5,200 new Wikipedia pages on COVID-19 were created, accumulating over 400 million page views by mid-June 2020. 1 At the same time, an unprecedented amount of scientific articles on COVID-19 and the ongoing pandemic have been published online. Wikipedia’s content is based on reliable sources, such as scientific literature. Given its public function, it is crucial for Wikipedia to rely on representative and reliable scientific results, especially in a time of crisis. We assess the coverage of COVID-19-related research in Wikipedia via citations to a corpus of over 160,000 articles. We find that Wikipedia editors are integrating new research at a fast pace, and have cited close to 2% of the COVID-19 literature under consideration. While doing so, they are able to provide a representative coverage of COVID-19-related research. We show that all the main topics discussed in this literature are proportionally represented from Wikipedia, after accounting for article-level effects. We further use regression analyses to model citations from Wikipedia and show that Wikipedia editors on average rely on literature that is highly cited, widely shared on social media, and peer-reviewed.

Countries
Netherlands, Denmark, Italy
Keywords

Coronavirus, Q1-390, Science (General), 330, Bibliometrics, Scientometrics, COVID-19, Bibliometrics; CORD-19; Coronavirus; COVID-19; Scientometrics; Wikipedia, CORD-19, Wikipedia

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    40
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
    OpenAIRE UsageCounts
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    download downloads 11
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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
40
Top 10%
Top 10%
Top 1%
79
11
Green
gold