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10.2196/21463

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suck abstract from ncbi


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pmid33481756      J+Med+Internet+Res 2021 ; 23 (2): e21463
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  • Factors Driving Citizen Engagement With Government TikTok Accounts During the COVID-19 Pandemic: Model Development and Analysis #MMPMID33481756
  • Chen Q; Min C; Zhang W; Ma X; Evans R
  • J Med Internet Res 2021[Feb]; 23 (2): e21463 PMID33481756show ga
  • BACKGROUND: During the COVID-19 pandemic, growth in citizen engagement with social media platforms has enabled public health departments to accelerate and improve health information dissemination, developing transparency and trust between governments and citizens. In light of these benefits, it is imperative to learn the antecedents and underlying mechanisms for this to maintain and enhance engagement. OBJECTIVE: The aim of this study is to determine the factors and influencing mechanisms related to citizen engagement with the TikTok account of the National Health Commission of China during the COVID-19 pandemic. METHODS: Using a web crawler, 355 short videos were collected from the Healthy China account on TikTok (with more than 3 million followers throughout China), covering the period from January 21, 2020, to April 25, 2020. The title and video length, as well as the number of likes, shares, and comments were collected for each video. After classifying them using content analysis, a series of negative binomial regression analyses were completed. RESULTS: Among the 355 videos, 154 (43.4%) related to guidance for clinicians, patients, and ordinary citizens, followed by information concerning the government's handling of the pandemic (n=100, 28.2%), the latest news about COVID-19 (n=61, 17.2%), and appreciation toward frontline emergency services (n=40, 11.3%). Video length, titles, dialogic loop, and content type all influenced the level of citizen engagement. Specifically, video length was negatively associated with the number of likes (incidence rate ratio [IRR]=0.19, P<.001) and comments (IRR=0.39, P<.001). Title length was positively related to the number of shares (IRR=24.25, P=.01), likes (IRR=8.50, P=.03), and comments (IRR=7.85, P=.02). Dialogic loop negatively predicted the number of shares (IRR=0.56, P=.03). In comparison to appreciative information, information about the government's handling of the situation (IRR=5.16, P<.001) and guidelines information (IRR=7.31, P<.001) were positively correlated with the number of shares, while the latest news was negatively related to the number of likes received (IRR=0.46, P=.004). More importantly, the relationship between predictors and citizen engagement was moderated by the emotional valence of video titles. Longer videos with positive titles received a higher number of likes (IRR=21.72, P=.04) and comments (IRR=10.14, P=.047). Furthermore, for short videos related to government handling of the pandemic (IRR=14.48, P=.04) and guidance for stakeholders (IRR=7.59, P=.04), positive titles received a greater number of shares. Videos related to the latest news (IRR=66.69, P=.04) received more likes if the video title displayed higher levels of positive emotion. CONCLUSIONS: During the COVID-19 pandemic, videos were frequently published on government social media platforms. Video length, title, dialogic loop, and content type significantly influenced the level of citizen engagement. These relationships were moderated by the emotional valence of the video's title. Our findings have implications for maintaining and enhancing citizen engagement via government social media.
  • |*COVID-19/epidemiology[MESH]
  • |*Emotions[MESH]
  • |*Federal Government[MESH]
  • |*Information Dissemination[MESH]
  • |*Pandemics[MESH]
  • |China/epidemiology[MESH]
  • |Health Education[MESH]
  • |Humans[MESH]
  • |Public Health Administration/*statistics & numerical data[MESH]
  • |Social Media/*statistics & numerical data[MESH]


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