COVID-19 information propagation dynamics in the Chinese Sina-microblog

Fulian Yin; Jiahui Lv; Xiaojian Zhang; Xinyu Xia; Jianhong Wu; Fulian Yin; Jiahui Lv; Xiaojian Zhang; Xinyu Xia; Jianhong Wu

doi:10.3934/mbe.2020146

Mathematical Biosciences and Engineering

2020, Volume 17, Issue 3: 2676-2692. doi: 10.3934/mbe.2020146

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Research article Special Issues

COVID-19 information propagation dynamics in the Chinese Sina-microblog

1.
College of Information and Communication Engineering, Communication University of China, Beijing,100024, China
2.
Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J1P3, Canada

Received: 09 February 2020 Accepted: 04 March 2020 Published: 09 March 2020

The outbreak of a novel coronavirus (COVID-19) generated an outbreak of public opinions in the Chinese Sina-microblog. To help in designing effective communication strategies during a major public health emergency, we propose a multiple-information susceptible-discussing-immune (M-SDI) model in order to understand the patterns of key information propagation on social networks. We develop the M-SDI model, based on the public discussion quantity and take into account of the behavior that users may re-enter another related topic or Weibo after discussing one. Data fitting using the real data of COVID-19 public opinion obtained from Chinese Sina-microblog can parameterize the model to make accurate prediction of the public opinion trend until the next major news item occurs. The reproduction ratio has fallen from 1.7769 and maintained around 0.97, which reflects the peak of public opinion has passed but it will continue for a period of time.
- COVID-19,
- dynamic model,
- prediction,
- Sina-microblog
Citation: Fulian Yin, Jiahui Lv, Xiaojian Zhang, Xinyu Xia, Jianhong Wu. COVID-19 information propagation dynamics in the Chinese Sina-microblog[J]. Mathematical Biosciences and Engineering, 2020, 17(3): 2676-2692. doi: 10.3934/mbe.2020146

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Abstract

The outbreak of a novel coronavirus (COVID-19) generated an outbreak of public opinions in the Chinese Sina-microblog. To help in designing effective communication strategies during a major public health emergency, we propose a multiple-information susceptible-discussing-immune (M-SDI) model in order to understand the patterns of key information propagation on social networks. We develop the M-SDI model, based on the public discussion quantity and take into account of the behavior that users may re-enter another related topic or Weibo after discussing one. Data fitting using the real data of COVID-19 public opinion obtained from Chinese Sina-microblog can parameterize the model to make accurate prediction of the public opinion trend until the next major news item occurs. The reproduction ratio has fallen from 1.7769 and maintained around 0.97, which reflects the peak of public opinion has passed but it will continue for a period of time.

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