Replication Data for: How Information Flows from the World to China|信息流动数据集|社交媒体分析数据集

Government censorship---internet shutdowns, blockages, firewalls---imposes significant barriers to the transnational flow of information despite the connective power of digital technologies. In this paper, we examine whether and how information flows across borders despite government censorship. We develop a semi-automated system that combines deep learning and human annotation to find co-occurring content across different social media platforms and languages. We use this system to detect co-occurring content between Twitter and Sina Weibo as Covid-19 spread globally, and we conduct in-depth investigations of co-occurring content to identify those that constitute an inflow of information from the global information ecosystem into China. We find that approximately one-fourth of content with relevance for China that gain widespread public attention on Twitter makes its way to Weibo. Unsurprisingly, Chinese state-controlled media and commercialized domestic media play a dominant role in facilitating these inflows of information. However, we find that Weibo users without traditional media or government affiliation are also an important mechanism for transmitting information into China. These results imply that while censorship combined with media control provides substantial leeway for the government to set the agenda, social media provides opportunities for non-institutional actors to influence the information environment. Methodologically, the system we develop offers an new approach for the quantitative analysis of cross-platform and cross-lingual communication.