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COVID-19 research in Wikipedia

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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 have been created and have accumulated over 400M pageviews 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 contents are 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 so 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 which is highly cited, widely shared on social media, and has been peer-reviewed.
Title: COVID-19 research in Wikipedia
Description:
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 have been created and have accumulated over 400M pageviews 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 contents are 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 so 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 which is highly cited, widely shared on social media, and has been peer-reviewed.

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