COVID-19的爆发对世界产生了巨大影响。确诊病例持续增加,对全世界的社会和经济造成损害。公众密切关注有关大流行的信息,并通过各种媒体了解该疾病。传播公众需要的全面准确的COVID-19信息有助于教育人们采取预防措施。
本研究旨在通过分析疫情期间《人民日报》官方微信发布的信息,考察COVID-19信息的传播情况。总结了中国阅读最多的COVID-19信息,并研究了影响信息传播的因素,以了解影响其传播的特征。此外,进行这项研究是为了确定如何有效传播COVID-19信息,并就如何在大流行期间管理舆论和信息治理提供建议.
这是一项基于微信公众号的回顾性研究。我们收集了所有与COVID-19相关的信息,从《人民日报》关于COVID-19的第一份报告开始,到最后一条关于解除中国34个省一级应急响应的信息结束。然后对这些信息进行了描述性分析,以及清博大数据的传播指数。根据各种特征和传播指数,采用多元线性回归方法研究影响信息传播的因素。
2020年1月19日至5月2日,《人民日报》发布了1984条信息;1621条与COVID-19有关,主要包括头条新闻,具有情感内容的项目,以及与大流行发展有关的问题。通过分析传播指数,发现了七个信息传播高峰。在COVID-19信息媒体显著性的三个维度中,内容,格式八因素影响COVID-19信息的传播。
不同类型的大流行相关信息具有不同的传播力。为了有效传播信息并防止COVID-19的传播,我们应该确定影响这种传播的因素。然后我们应该传播公众最关心的信息类型,利用信息教育人们提高健康素养,改善舆论和信息治理。
The COVID-19 outbreak has tremendously impacted the world. The number of confirmed cases has continued to increase, causing damage to society and the economy worldwide. The public pays close attention to information on the pandemic and learns about the disease through various media outlets. The dissemination of comprehensive and accurate COVID-19 information that the public needs helps to educate people so they can take preventive measures.
This study aimed to examine the dissemination of COVID-19 information by analyzing the information released by the official WeChat account of the People\'s Daily during the pandemic. The most-read COVID-19 information in China was summarized, and the factors that influence information dissemination were studied to understand the characteristics that affect its dissemination. Moreover, this was conducted in order to identify how to effectively disseminate COVID-19 information and to provide suggestions on how to manage public opinion and information governance during a pandemic.
This was a retrospective study based on a WeChat official account. We collected all COVID-19-related information, starting with the first report about COVID-19 from the People\'s Daily and ending with the last piece of information about lifting the first-level emergency response in 34 Chinese provinces. A descriptive analysis was then conducted on this information, as well as on Qingbo Big Data\'s dissemination index. Multiple linear regression was utilized to study the factors that affected information dissemination based on various characteristics and the dissemination index.
From January 19 to May 2, 2020, the People\'s Daily released 1984 pieces of information; 1621 were related to COVID-19, which mainly included headline news items, items with emotional content, and issues related to the pandemic\'s development. By analyzing the dissemination index, seven information dissemination peaks were discerned. Among the three dimensions of COVID-19 information-media salience, content, and format-eight factors affected the spread of COVID-19 information.
Different types of pandemic-related information have varying dissemination power. To effectively disseminate information and prevent the spread of COVID-19, we should identify the factors that affect this dissemination. We should then disseminate the types of information the public is most concerned about, use information to educate people to improve their health literacy, and improve public opinion and information governance.