论文标题
微博-COV：来自微博的大规模COVID-19社交媒体数据集
Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Weibo
论文作者
论文摘要
随着世界各地Covid-19的迅速发展，要求人们维持“社交距离”和“留在家里”。在这种情况下，广泛的社交互动转移到网络空间，尤其是在Twitter和Sina Weibo等社交媒体平台上。人们在大流行爆发期间生成帖子以共享信息，表达意见并寻求帮助，而社交媒体上的这些数据对于预防Covid-19传播（例如预警和爆发检测）来说是有价值的。因此，在本文中，我们发行了从Sina Weibo收集的新颖且细粒度的大规模Covid-19社交媒体数据集（名为Weibo-Cov），其中包含超过4000万个帖子，范围从2019年12月1日至2020年4月30日。我们希望该数据集能够从多个角度促进Covid-19的研究，并能够更好地进行研究以抑制这一大流行的传播。
With the rapid development of COVID-19 around the world, people are requested to maintain "social distance" and "stay at home". In this scenario, extensive social interactions transfer to cyberspace, especially on social media platforms like Twitter and Sina Weibo. People generate posts to share information, express opinions and seek help during the pandemic outbreak, and these kinds of data on social media are valuable for studies to prevent COVID-19 transmissions, such as early warning and outbreaks detection. Therefore, in this paper, we release a novel and fine-grained large-scale COVID-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 like post-level information, interactive information, location information, and repost network. We hope this dataset can promote studies of COVID-19 from multiple perspectives and enable better and rapid researches to suppress the spread of this pandemic.
