Penn Medicine Center for Digital Health, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, Pennsylvania.
Penn Medicine Center for Digital Health, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Computer and Information Science, University of Pennsylvania, Philadelphia, Pennsylvania.
J Adolesc Health. 2021 Aug;69(2):234-241. doi: 10.1016/j.jadohealth.2021.05.010. Epub 2021 Jun 22.
The purpose of this study was to characterize COVID-19 content posted by users and disseminated via TikTok, a social media platform that has become known largely as an entertainment platform for viral video-sharing. We sought to capture how TikTok videos posted during the initial months of the COVID pandemic changed over time as cases accelerated.
This study is an observational analysis of sequential TikTok videos with #coronavirus from January to March 2020. Videos were independently coded to assess content (e.g., health relatedness, humor, fear, empathy), misinformation, and public sentiment. To assess engagement, we also codified how often videos were shared relative to their content.
We coded 750 videos and approximately one in four videos tagged with #coronavirus featured health-related content such as featuring objects such as face masks, hand sanitizer, and other cleaning products. Most videos evoked "humor/parody," whereas 15% and 6% evoked "fear" and "empathy", respectively. TikTok videos posted in March 2020 had the largest number of shares and comments compared with January and February 2020. The proportion of shares and comments for "misleading and incorrect information" featured in videos was lower in March than in January and February 2020. There was no statistical difference between the share and comment counts of videos coded as "incorrect/incomplete" and "correct" over the entire time period.
Analyzing readily available social media platforms, such as TikTok provides real-time insights into public views, frequency and types of misinformation, and norms toward COVID-19. Analyzing TikTok videos has the potential to be used to inform public health messaging and public health mitigation strategies.
本研究的目的是描述用户在 TikTok 上发布的 COVID-19 内容,并传播这些内容,TikTok 是一个社交媒体平台,主要以病毒式视频分享的娱乐平台而闻名。我们试图捕捉 COVID 大流行初期,随着病例的加速,TikTok 视频是如何随时间变化的。
这是一项对 2020 年 1 月至 3 月期间带有#coronavirus 标签的 TikTok 视频的观察性分析。视频是独立编码的,以评估内容(例如与健康相关、幽默、恐惧、同情)、错误信息和公众情绪。为了评估参与度,我们还对视频相对于其内容的共享频率进行了编码。
我们对 750 个视频进行了编码,大约四分之一的带有#coronavirus 标签的视频以健康相关内容为特色,例如展示口罩、洗手液和其他清洁产品等物品。大多数视频唤起了“幽默/模仿”,而 15%和 6%分别唤起了“恐惧”和“同情”。与 2020 年 1 月和 2 月相比,2020 年 3 月发布的 TikTok 视频分享次数和评论最多。视频中“误导性和不正确信息”的分享和评论比例在 3 月比 1 月和 2 月低。在整个时间段内,被编码为“不正确/不完整”和“正确”的视频的分享和评论计数之间没有统计学差异。
分析 TikTok 等现成的社交媒体平台,可以实时了解公众观点、错误信息的频率和类型,以及对 COVID-19 的看法。分析 TikTok 视频有可能被用于为公共卫生信息传递和公共卫生缓解策略提供信息。