W eibo- COV : A Large-Scale COVID -19 Social Media Dataset from W eibo (2020)

Abstract: 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.

## introduction at the beginning of this writing, covid-19, an infectious disease caused by a coronavirus discovered in december, 2019, which also known as severe acute respiratory syndrome coronavirus 2 (sars-cov-2), has caused 4,517,399 individuals infected globally, with a death toll of @xcite . under the circumstance, the physical aspects of connection and human communication outside the household among people are limited considerably and mainly depend on digital devices like mobile phones or laptop computers @xcite . due to it, people keep staying at home and spending more time on social media communication, making social media a vital avenue for information sharing, opinions expression, and help-seeking @xcite . all that makes social media platforms like weibo, twitter, facebook and youtube a more vital sources of information during the pandemic. in previous studies, social media was considered a valuable data source for research against disease, like uncovering the dynamics of an emerging outbreak @xcite , predicting the flu activity, and disease surveillance @xcite . for example, some studies facilitate better influenza surveillance, like early warning and outbreaks detection @xcite , forecasting estimates of influenza activity @xcite , and predicting the actual number of infected cases @xcite . hence, it is necessary to retrieve the relevant social media datasets and make it freely accessible for researchers, for the sake of public goods and facilitating the relevant studies of covid-19. in this paper, we release a novel large-scale covid-19 social media dataset from sina weibo (akin to twitter), one of the most popular chinese social media platforms in china. for convenience, we named it weibo-cov, which contains more than 40 million posts from december 1, 2019 to april 30, 2020. specifically, unlike the traditional api-based data collection methods, which limit large-scale data access, in this study, we construct a high-quality weibo active user pool with 20 million active users from over 250 million users, then collect all active users' posts during that period, followed by filtering covid-19 related posts with 179 representative keywords. moreover, the fields of posts in the dataset are fine-grained, including post-level information, interactive information, location information and repost network, etc. we hope this dataset can facilitate studies of covid-19 from multiple perspectives and enable better and rapid research to suppress the spread of this disease. ## related work several works have focused on creating social media datasets for enabling covid-19 research. @xcite , @xcite and @xcite have already released datasets collected from twitter. however, these datasets are mainly in english, and posts generated by chinese, the epicentre of the early development of covid-19, also deserves close attention. therefore, collecting the weibo datasets are also valuable and can provide additional supplements for researches. only one dataset proposed by @xcite ) includes posts from weibo, but their method relies on weibo advanced search api provided by weibo, which hinders them from collecting largescale posts as we mentioned above. compared with our dataset, the data size (less than 200k), the time period (from january 20, 2020 to march 24, 2020), and the number of keywords (only four keywords) of this weibo dataset seem much smaller and narrow. ## conclusion in this paper, we release weibo-cov, a first largescale covid-19 posts dataset from weibo. the dataset contains more than 40 million posts from december 1, 2019 to april 30, 2020, with rich field information. we hope this dataset could promote and facilitate related studies on covid-19.