How Information Flows from the World to China
How Information Flows from the World to China
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DOI：
10.1177/19401612221117470
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发表时间：
2022-08
期刊：
影响因子：
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通讯作者：
Yingda Lu;Jack Schaefer;Kunwoo Park;Jungseock Joo;Jennifer Pan
中科院分区：
文献类型：
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作者：
Yingda Lu;Jack Schaefer;Kunwoo Park;Jungseock Joo;Jennifer Pan
尽管数字技术具有强大的连接力，但政府的审查互联网的关闭、封锁、防火墙对信息的跨国流动造成了重大障碍。在本文中，我们将研究信息是否以及如何在政府审查的情况下跨境流动。我们开发了一个半自动化的系统，结合了深度学习和人工注释，可以在不同的社交媒体平台和语言中找到共同出现的内容。我们使用这一系统来检测新冠肺炎在全球蔓延时Twitter和新浪微博之间的共现内容，并对共现内容进行深入调查，以识别那些构成全球信息生态系统信息流入中国的内容。我们发现，在Twitter上获得广泛公众关注的与中国相关的内容中，约有四分之一进入了微博。毫不奇怪，中国国家控制的媒体和商业化的国内媒体在促进这些信息流入方面发挥了主导作用。然而，我们发现，没有传统媒体或政府背景的微博用户也是向中国传递信息的重要机制。这些结果意味着，虽然审查与媒体控制相结合，为政府制定议程提供了很大的回旋余地，但社交媒体为非机构行为者提供了影响信息环境的机会。在方法论上，我们开发的系统提供了一个新的方法，跨平台和跨语言的交流的定量分析。
Government censorship—internet shutdowns, blockages, firewalls—impose 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 gains 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 affiliations are also an important mechanism for transmitting information into China. These results imply that while censorship combined with media control provide 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 a new approach for the quantitative analysis of cross-platform and cross-lingual communication.