中国背景下的“平行大流行”：新冠疫情期间谣言及辟谣信息在中国社交媒体上的传播
The "Parallel Pandemic" in the Context of China: The Spread of Rumors and Rumor-Corrections During COVID-19 in Chinese Social Media.
作者信息
Song Yunya, Kwon K Hazel, Lu Yin, Fan Yining, Li Baiqi
机构信息
Hong Kong Baptist University, Kowloon, Hong Kong.
Arizona State University, Phoenix, AZ, USA.
出版信息
Am Behav Sci. 2021 Dec;65(14):2014-2036. doi: 10.1177/00027642211003153.
Although studies have investigated cyber-rumoring previous to the pandemic, little research has been undertaken to study rumors and rumor-corrections during the COVID-19 (coronavirus disease 2019) pandemic. Drawing on prior studies about how online stories become viral, this study will fill that gap by investigating the retransmission of COVID-19 rumors and corrective messages on Sina Weibo, the largest and most popular microblogging site in China. This study examines the impact of rumor types, content attributes (including frames, emotion, and rationality), and source characteristics (including follower size and source identity) to show how they affect the likelihood of a COVID-19 rumor and its correction being shared. By exploring the retransmission of rumors and their corrections in Chinese social media, this study will not only advance scholarly understanding but also reveal how corrective messages can be crafted to debunk cyber-rumors in particular cultural contexts.
尽管此前已有研究在疫情大流行之前对网络谣言进行过调查，但针对2019冠状病毒病（COVID-19）大流行期间的谣言及谣言辟谣开展的研究却很少。借鉴此前关于网络故事如何迅速传播的研究，本研究将通过调查COVID-19谣言及辟谣信息在中国最大且最受欢迎的微博网站——新浪微博上的转发情况来填补这一空白。本研究考察谣言类型、内容属性（包括框架、情感和合理性）以及来源特征（包括粉丝数量和来源身份）的影响，以展示它们如何影响COVID-19谣言及其辟谣信息被分享的可能性。通过探究中文社交媒体中谣言及其辟谣信息的转发情况，本研究不仅将增进学术理解，还将揭示在特定文化背景下如何精心制作辟谣信息以揭穿网络谣言。
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