Modeling and Quantifying the Role of User Active Search in COVID-19 Multi-Information Analysis and Prediction in the Chinese Sina-microblog

Le résumé fourni par la source

The study of information spreading is important and necessary, especially during the Coronavirus, when plenty of opinions aroused in the Chinese Sina-microblog. On the basis of previous studies, we propose a comprehensive susceptible-reading-forwarding-immune (SRFI) model with considering user active search. We establish differential equations introducing average active reading rate to describe the multi-information propagation process. By using typical event about COVID-19 during the outbreak of public opinion to carry out the numerical fitting experiment to estimate model parameters, fit real data, and analyze the calculated information transmission indexes, we verify the validity of the model. We analyze the sensitivity of multiple parameters to multi-information transmission index based on reading and forwarding and the effect of average active reading rate to show the influence of the new parameter on multi-information transmission. In addition, to compare the predictive ability of the previous model with our new model, we use the early prediction method. Result shows that our new model can forecast the process of multi-information transmission faster and more exactly. The conclusions above indicate that the role of user active search is not negligible and the I-SRFI model can help us design effective communication strategies for rapid implementation of public health interventions.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.