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With the rapid development of COVID-19 around the world, people are requestedto maintain "social distance" and "stay at home". In this scenario, extensivesocial interactions transfer to cyberspace, especially on social mediaplatforms like Twitter and Sina Weibo. People generate posts to shareinformation, express opinions and seek help during the pandemic outbreak, andthese kinds of data on social media are valuable for studies to preventCOVID-19 transmissions, such as early warning and outbreaks detection.Therefore, in this paper, we release a novel and fine-grained large-scaleCOVID-19 social media dataset collected from Sina Weibo, named Weibo-COV,contains more than 40 million posts ranging from December 1, 2019 to April 30,2020. Moreover, this dataset includes comprehensive information nuggets likepost-level information, interactive information, location information, andrepost network. We hope this dataset can promote studies of COVID-19 frommultiple perspectives and enable better and rapid researches to suppress thespread of this pandemic.

Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Weibo