During the COVID-19 pandemic, people look for coronavirus information to keep their health. However, the more information is in demand, the more rumors and misinformation spread. We call this phenomenon an Infodemic. According to Wikipedia, infodemic is a hybrid word of “information” and “epidemic.” It typically refers to a rapid and far-reaching spread of accurate and inaccurate information about something, such as a disease. To mitigate the harmful impact of infodemics, we need to identify what information the public wants and provide reliable information as quickly as possible.

The Data Science Group of IBS detected public interest in COVID-19 from Wikipedia. By collaborating with Wikimedia Foundation and Max Planck Institute for Human Development, Berlin, Germany, we developed a novel method to retrieve COVID-19 topic related items.

The COVID-19 Wikipedia data is available in Figshare ( for further research. Also, the code that generates topic related data in Wikipedia is available on Github (Code: For further analysis, have a look at the video above.


September 1 (Wed), 2021

You can take a look at the summary of our recent updates(*in Korean):

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Accessing accurate information is essential to reduce the social damage caused by the COVID-19 pandemic. The information about ongoing events like COVID-19 is quickly updated in Wikipedia, which is an accessible internet encyclopedia that allows users to edit it themselves. However, the existing Wikipedia information retrieval method has a limitation in collecting information including relationships between documents. The template format of Wikipedia reflects the structure of information as a link that is selectively applied to documents with high relevance.

In this study, information on COVID-19 in 10 languages Wikipedia was collected using a template and reorganized into networks. The data and code are available on Github(