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Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study

机译：了解Covid-19大流行期间关于疾病控制和预防中心的公众讨论使用Twitter数据：文本挖掘分析研究

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BackgroundThe Centers for Disease Control and Prevention (CDC) is a national public health protection agency in the United States. With the escalating impact of the COVID-19 pandemic on society in the United States and around the world, the CDC has become one of the focal points of public discussion. ObjectiveThis study aims to identify the topics and their overarching themes emerging from the public COVID-19-related discussion about the CDC on Twitter and to further provide insight into public's concerns, focus of attention, perception of the CDC's current performance, and expectations from the CDC. MethodsTweets were downloaded from a large-scale COVID-19 Twitter chatter data set from March 11, 2020, when the World Health Organization declared COVID-19 a pandemic, to August 14, 2020. We used R (The R Foundation) to clean the tweets and retain tweets that contained any of five specific keywords—cdc, CDC, centers for disease control and prevention, CDCgov, and cdcgov—while eliminating all 91 tweets posted by the CDC itself. The final data set included in the analysis consisted of 290,764 unique tweets from 152,314 different users. We used R to perform the latent Dirichlet allocation algorithm for topic modeling. ResultsThe Twitter data generated 16 topics that the public linked to the CDC when they talked about COVID-19. Among the topics, the most discussed was COVID-19 death counts, accounting for 12.16% (n=35,347) of the total 290,764 tweets in the analysis, followed by general opinions about the credibility of the CDC and other authorities and the CDC's COVID-19 guidelines, with over 20,000 tweets for each. The 16 topics fell into four overarching themes: knowing the virus and the situation, policy and government actions, response guidelines, and general opinion about credibility. ConclusionsSocial media platforms, such as Twitter, provide valuable databases for public opinion. In a protracted pandemic, such as COVID-19, quickly and efficiently identifying the topics within the public discussion on Twitter would help public health agencies improve the next-round communication with the public.
机译：背景技术疾病控制和预防中心（CDC）是美国国家公共卫生保护机构。 CDC在美国和世界各地社会对社会的影响升级，并成为公众讨论的联络点之一。客观的研究旨在识别从公共COVID-19相关讨论的主题和他们的总体主题关于Twitter上的CDC和进一步了解公众关注，关注，对CDC目前的表现的看法以及期望的洞察力CDC。从2020年3月11日，世界卫生组织宣布Covid-19大流行，到2020年8月14日，从大型Covid-19 Twitter Chatter数据下载。我们使用了R（R基础）来清洁推文和保留包含五种特定关键词 - CDC，CDC，疾病控制和预防中心的推文，CDCGOV和CDCGOV- - 消除CDC本身发布的所有91条推文。分析中包含的最终数据集由来自152,314个不同用户的290,764个独特的推文组成。我们使用R执行主题建模的潜在Dirichlet分配算法。结果是Twitter数据生成16个主题，即在谈论Covid-19时，公众链接到CDC。在主题中，讨论最多的是Covid-19死亡计数，占分析中的290,764条推文的12.16％（n = 35,347），其次是关于CDC和其他当局和CDC的Covid的一般性意见和CDC的Covid- 19指南，每次有超过20,000名推文。 16个主题陷入了四个总体主题：了解病毒以及情况，政策和政府行为，响应指导方针，以及对可信度的一般性意见。结论社会媒体平台，如Twitter，为舆论提供有价值的数据库。在持续的大流行病中，如Covid-19，快速有效地识别Twitter上公众讨论中的主题将有助于公共卫生机构改善与公众的下一轮沟通。

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