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Effects of Health Information Dissemination on User Follows and Likes during COVID-19 Outbreak in China: Data and Content Analysis

Author

Listed:
  • Rongyang Ma

    (School of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan 430030, China)

  • Zhaohua Deng

    (School of Medicine and Health Management, Huazhong University of Science and Technology, Wuhan 430030, China)

  • Manli Wu

    (School of Journalism and Information Communication, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

Background : 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. Methods : 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. Results: 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. Conclusions : 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.

Suggested Citation

  • Rongyang Ma & Zhaohua Deng & Manli Wu, 2020. "Effects of Health Information Dissemination on User Follows and Likes during COVID-19 Outbreak in China: Data and Content Analysis," IJERPH, MDPI, vol. 17(14), pages 1-21, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:14:p:5081-:d:384512
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    References listed on IDEAS

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    1. Kelly, Ann H. & Lezaun, Javier & Löwy, Ilana & Matta, Gustavo Corrêa & de Oliveira Nogueira, Carolina & Rabello, Elaine Teixeira, 2020. "Uncertainty in times of medical emergency: Knowledge gaps and structural ignorance during the Brazilian Zika crisis," Social Science & Medicine, Elsevier, vol. 246(C).
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    Cited by:

    1. Mélanie Suppan & Loric Stuby & Christophe Alain Fehlmann & Mohamed Abbas & Sophia Achab & Stephan Harbarth & Laurent Suppan, 2022. "The Impact of Three Communication Channels on the Dissemination of a Serious Game Designed to Enhance COVID-19 Prevention," IJERPH, MDPI, vol. 19(16), pages 1-8, August.
    2. Yi Yang & Wen Deng & Yi Zhang & Zijun Mao, 2020. "Promoting Public Engagement during the COVID-19 Crisis: How Effective Is the Wuhan Local Government’s Information Release?," IJERPH, MDPI, vol. 18(1), pages 1-17, December.
    3. Santiago Tejedor & Laura Cervi & Fernanda Tusa & Marta Portales & Margarita Zabotina, 2020. "Information on the COVID-19 Pandemic in Daily Newspapers’ Front Pages: Case Study of Spain and Italy," IJERPH, MDPI, vol. 17(17), pages 1-16, August.

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