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COVID-19 research in Wikipedia
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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.
Title: COVID-19 research in Wikipedia
Description:
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.
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