Kreps Sarah, George Julie, Watson Noah, Cai Gloria, Ding Keyi
Department of Government Cornell University Ithaca, NY United States.
Department of Information Science Cornell University Ithaca, NY United States.
JMIR Infodemiology. 2022 Feb 24;2(1):e31793. doi: 10.2196/31793. eCollection 2022 Jan-Jun.
Misinformation about COVID-19 on social media has presented challenges to public health authorities during the pandemic. This paper leverages qualitative and quantitative content analysis on cross-platform, cross-national discourse and misinformation in the context of COVID-19. Specifically, we investigated COVID-19-related content on Twitter and Sina Weibo-the largest microblogging sites in the United States and China, respectively.
Using data from 2 prominent microblogging platform, Twitter, based in the United States, and Sina Weibo, based in China, we compared the content and relative prevalence of misinformation to better understand public discourse of public health issues across social media and cultural contexts.
A total of 3,579,575 posts were scraped from both Sina Weibo and Twitter, focusing on content from January 30, 2020, within 24 hours of when WHO declared COVID-19 a "public health emergency of international concern," and a week later, on February 6, 2020. We examined how the use and engagement measured by keyword frequencies and hashtags differ across the 2 platforms. A 1% random sample of tweets that contained both the English keywords "coronavirus" and "covid-19" and the equivalent Chinese characters was extracted and analyzed based on changes in the frequencies of keywords and hashtags and the Viterbi algorithm. We manually coded a random selection of 5%-7% of the content to identify misinformation on each platform and compared posts using the WHO fact-check page to adjudicate accuracy of content.
Both platforms posted about the outbreak and transmission, but posts on Sina Weibo were less likely to reference topics such as WHO, Hong Kong, and death and more likely to cite themes of resisting, fighting, and cheering against coronavirus. Misinformation constituted 1.1% of Twitter content and 0.3% of Sina Weibo content-almost 4 times as much on Twitter compared to Sina Weibo.
Quantitative and qualitative analysis of content on both platforms points to lower degrees of misinformation, more content designed to bolster morale, and less reference to topics such as WHO, death, and Hong Kong on Sina Weibo than on Twitter.
在疫情期间，社交媒体上关于新冠病毒的错误信息给公共卫生当局带来了挑战。本文在新冠疫情背景下，对跨平台、跨国的言论及错误信息进行定性和定量内容分析。具体而言，我们分别调查了美国最大的微博网站推特（Twitter）和中国最大的微博网站新浪微博上与新冠病毒相关的内容。
利用来自美国的推特和中国的新浪微博这两个知名微博平台的数据，我们比较了错误信息的内容和相对流行程度，以更好地了解跨社交媒体和文化背景下关于公共卫生问题的公众话语。
从新浪微博和推特上总共抓取了3579575条帖子，重点关注2020年1月30日（即世界卫生组织宣布新冠病毒为“国际关注的突发公共卫生事件”之时）及一周后的2020年2月6日这24小时内的内容。我们研究了通过关键词频率和主题标签衡量的使用和参与度在这两个平台上是如何不同的。抽取了1%的既包含英文关键词“coronavirus”和“covid - 19”又包含相应中文字符的推文样本，基于关键词和主题标签频率的变化以及维特比算法进行分析。我们手动对随机抽取的5% - 7%的内容进行编码，以识别每个平台上的错误信息，并使用世界卫生组织事实核查页面比较帖子，以判定内容的准确性。
两个平台都发布了有关疫情爆发和传播的内容，但新浪微博上的帖子提及世界卫生组织、香港和死亡等话题的可能性较小，而更有可能引用抗击、对抗和为抗击新冠病毒欢呼等主题。错误信息在推特内容中占1.1%，在新浪微博内容中占0.3%——推特上的错误信息几乎是新浪微博的4倍。
对两个平台内容的定量和定性分析表明，新浪微博上错误信息的程度较低，更多内容旨在鼓舞士气，且提及世界卫生组织、死亡和香港等话题的频率低于推特。
