With the rapid development of COVID-19, people are asked to maintain "social distance" and "stay at home". In this scenario, more and more social interactions move online, especially on social media like Twitter and Weibo. People post tweets to share information, express opinions and seek help during the pandemic, and these tweets on social media are valuable for studies against COVID-19 , such as early warning and outbreaks detection. Therefore, in this paper, we release a  large-scale COVID-19 social media dataset from Weibo called Weibo-COV, covering more than 30 million tweets from 1 November 2019 to 30 April 2020. Moreover, the field information of the dataset is very rich, including basic tweets information, interactive information, location information and retweet network. We hope this dataset can promote studies of COVID-19 from multiple perspectives and enable better and faster researches to suppress the spread of this disease.
With the rapid development of COVID-19, people are asked to maintain "social distance" and "stay at home". In this scenario, more and more social interactions move online, especially on social media like Twitter and Weibo. People post tweets to share information, express opinions and seek help during the pandemic, and these tweets on social media are valuable for studies against COVID19 , such as early warning and outbreaks detection. Therefore, in this paper, we release a novel large-scale COVID-19 social media dataset from Weibo called Weibo-COV, covering more than 40 million tweets from 1 December 2019 to 30 April 2020. Moreover, the field information of the dataset is very rich, including basic tweets information, interactive information, location information and retweet network. We hope this dataset can promote studies of COVID-19 from multiple perspectives and enable better and faster researches to suppress the spread of this disease.
R
COVID-19
COVID19
A
novel
R
30
40
R
November
December