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Real-world Islands in a Social Media Sea: Nationalism and Censorship on Weibo during the 2012 Diaoyu/Senkaku Crisis*

Published online by Cambridge University Press:  19 January 2016

Christopher Cairns  and
Allen Carlson
Christopher Cairns*
Affiliation:
Cornell University.
Allen Carlson
Affiliation:
Cornell University.
*
Email: [email protected] (corresponding author).
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Abstract

During August and September 2012, Sino-Japanese conflict over the Diaoyu/Senkaku Islands escalated. Alongside street demonstrations in China, there was an outpouring of public sentiment on China's leading micro-blog, Sina Weibo (微波). Using human and computer-assisted content analysis, we exploit original Weibo data to measure how public sentiment in China fluctuated over the dispute, and ask two questions. First, how cohesive and volatile were online nationalist sentiments? Second, we measure government censorship of Weibo in order to ask which sentiments did authorities allow to be expressed, and when? We first find that many of the micro-bloggers' harshest invective was directed not at Japan but at their own government. Second, while censorship remained high across topics for most of the dispute, it plummeted on 18 August – the same day as bloggers' anger at Beijing peaked. These observations suggest three theoretical explanations: two are instrumental-strategic (“audience costs” and “safety valve”) and one is ideational (elite identification with protesters).

摘要

中日钓鱼岛 (尖阁列岛) 冲突在2012年八九月间突然升级。在中国大陆既发生了街头示威, 又在新浪微博上出现了公众情绪的大爆发。我们通过人工和电脑辅助的内容分析方法利用微博原始数据来衡量整个争端中中国公众情绪的波动。我们提出两个问题: 第一, 网络民族主义情绪的凝聚力和变动性如何? 第二, 我们衡量中国政府对微博的审查, 从而进一步提问:哪些情绪在什么时候会被政府允许表达? 我们有两项主要发现: 第一, 许多微博发布者最尖锐的批评不是针对日本, 而是针对本国政府; 第二, 虽然政府在争端过程中绝大多数时间对于不同话题的审查都极为严格, 但8月18日审查力度突然直线下跌, 而这一天微博发布者针对北京政权的愤怒也正好达到顶峰。以上观察验证了以下三种理论解释, 包括两种工具性和战略性理论 (观众成本理论和减压阀理论) 和一种观念性理论 (精英对于抗议者诉求的认同)。

Keywords

social mediaChinaWeibo: nationalismcensorshipDiaoyu IslandsJapan社会化媒体新浪微博民族主义网络审查钓鱼岛日本
Type
Articles
Information
The China Quarterly , Volume 225 , March 2016 , pp. 23 - 49
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Copyright
Copyright © The China Quarterly 2016 

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Footnotes

*

We would like to thank King-Wa Fu, Chung-Hong Chan and Michael Chau at the University of Hong Kong for their efforts on the WeiboScope project, which produced the dataset we use. We would also like to thank Jing Li, who served on our coding team.

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