School of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan 430030, China.
School of Journalism and Information Communication, Huazhong University of Science and Technology, Wuhan 430074, China.
Int J Environ Res Public Health. 2020 Jul 14;17(14):5081. doi: 10.3390/ijerph17145081.
: COVID-19 has greatly attacked China, spreading in the whole world. Articles were posted on many official WeChat accounts to transmit health information about this pandemic. The public also sought related information via social media more frequently. However, little is known about what kinds of information satisfy them better. This study aimed to explore the characteristics of health information dissemination that affected users' information behavior on WeChat. : Two-wave data were collected from the top 200 WeChat official accounts on the Xigua website. The data included the change in the number of followers and the total number of likes on each account in a 7-day period, as well as the number of each type of article and headlines about coronavirus. It was used to developed regression models and conduct content analysis to figure out information characteristics in quantity and content. For nonmedical institution accounts in the model, report and story types of articles had positive effects on users' following behaviors. The number of headlines on coronavirus positively impacts liking behaviors. For medical institution accounts, report and science types had a positive effect, too. In the content analysis, several common characteristics were identified. : Characteristics in terms of the quantity and content in health information dissemination contribute to users' information behavior. In terms of the content in the headlines, via coding and word frequency analysis, organizational structure, multimedia applications, and instructions-the common dimension in different articles-composed the common features in information that impacted users' liking behaviors.
新冠疫情重创中国，并在全球蔓延。许多官方微信公众号发布了大量有关该流行病的健康信息文章。公众也更频繁地通过社交媒体寻求相关信息。然而，人们对什么样的信息能更好地满足他们的需求知之甚少。本研究旨在探讨影响用户微信信息行为的健康信息传播特征。
本研究通过两轮数据收集，从西瓜网站上的前 200 个微信官方账号中获取数据。数据包括每个账号在 7 天内粉丝数量和总点赞数的变化，以及每类关于冠状病毒的文章和标题数量。利用这些数据建立回归模型并进行内容分析，以了解数量和内容方面的信息特征。
对于模型中的非医疗机构账号，报道和故事类型的文章对用户的关注行为有积极影响。冠状病毒标题的数量对点赞行为有积极影响。对于医疗机构账号，报道和科学类型也有积极影响。在内容分析中，确定了几个共同特征。
健康信息传播在数量和内容方面的特征有助于用户的信息行为。就标题内容而言，通过编码和词频分析、组织结构、多媒体应用以及指令——不同文章中的共同维度——构成了影响用户点赞行为的信息的共同特征。
