Center for Information Systems and Technology, Claremont Graduate University, Claremont, CA, USA.
School of Community and Global Health, Claremont Graduate University, Claremont, CA, USA.
Disaster Med Public Health Prep. 2022 Oct;16(5):1881-1888. doi: 10.1017/dmp.2021.65. Epub 2021 Mar 3.
To characterize and compare early coverage of coronavirus disease 2019 (COVID-19) in newspapers, television, and social media, and discuss implications for public health communication strategies that are relevant to an initial pandemic response.
Latent Dirichlet allocation (LDA), an unsupervised topic modeling technique, analysis of 3271 newspaper articles, 40 cable news shows transcripts, 96,000 Twitter posts, and 1000 Reddit posts during March 4-12, 2020, a period chronologically early in the timeframe of the COVID-19 pandemic.
Coverage of COVID-19 clustered on topics such as epidemic, politics, and the economy, and these varied across media sources. Topics dominating news were not predominantly health-related, suggesting a limited presence of public health in news coverage in traditional and social media. Examples of misinformation were identified, particularly in social media.
Public health entities should use communication specialists to create engaging informational content to be shared on social media sites. Public health officials should be attuned to their target audience to anticipate and prevent spread of common myths likely to exist within a population. This may help control misinformation in early stages of pandemics.
描述并比较 2019 年冠状病毒病(COVID-19)在报纸、电视和社交媒体上的早期报道,讨论与初始大流行应对相关的公共卫生传播策略的影响。
使用潜在狄利克雷分配(LDA),一种无监督的主题建模技术,对 2020 年 3 月 4 日至 12 日期间的 3271 篇报纸文章、40 个有线电视新闻节目记录、96000 条 Twitter 帖子和 1000 条 Reddit 帖子进行分析,这一时间点处于 COVID-19 大流行的早期阶段。
COVID-19 的报道集中在疫情、政治和经济等主题上,这些主题在不同的媒体来源中有所不同。主导新闻的主题并非主要与健康相关,这表明传统和社交媒体的新闻报道中公共卫生的参与度有限。在社交媒体中发现了一些错误信息的例子。
公共卫生实体应利用传播专家在社交媒体网站上分享引人入胜的信息内容。公共卫生官员应该了解其目标受众,以预测和防止在人群中传播可能存在的常见神话。这可能有助于在大流行的早期阶段控制错误信息。