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DR-SCIR Public Opinion Propagation Model with Direct Immunity and Social Reinforcement Effect by Li, Weidong; Guo, Tianyi; Wang, Yunming; Chen, Bo is a Mathematics article available to read on EtoBox.

What is DR-SCIR Public Opinion Propagation Model with Direct Immunity and Social Reinforcement Effect about?

The DR-SCIR network public opinion propagation model was employed to study the characters of S-state users stopping transmitting information for the first time and secondary transmission of immune users. The model takes into account symmetry and complexity such as direct immunization and social reinforcement effect, proposes the probability of direct immunity Psr and the probability of transform from the immune state to the hesitant state Prc, and divides public opinion information into positive public opinion and negative public opinion based on whether the public opinion information is confirmed. Simulation results show that, when direct immunity Psr = 0.5, the density of I-state nodes in the model decreased by 54.12% at the peak index; when the positive social reinforcement effect factor b = 10, the density of I-state nodes in the model increased by 16.67% at the peak index; and when the negative social reinforcement effect factor b = -10, the density of I-state nodes in the model decreased by 55.36% at the peak index. It shows that increasing the positive social reinforcement effect factor b can promote the spread of positive public opinion, reducing the negative social reinfor

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Author

Li, Weidong; Guo, Tianyi; Wang, Yunming; Chen, Bo

Publisher

MDPI AG; Multidisciplinary Digital Publishing Institute (MDPI); Basel: Molecular Diversity Preservation International (MDPI), 2009- (ISSN 2073-8994)

Published

2020

Language

EN

Field

Mathematics (Physical Sciences)