Construction of a Network Public Opinion Reversal Dissemination Model Considering the Role of Social Reinforcement

DOI

10.2991/978-94-6463-562-1_29How to use a DOI?

Keywords

Public Opinion Reversal; Social Reinforcement; Two-Stage Dissemination Dynamics Model; Simulation Analysis

Abstract

In recent years, public opinion reversal events in online networks have occurred frequently. These events often lead to the misguidance of netizens’ emotions, which not only undermines the credibility of the event’s main subjects and the media but also severely impacts social stability. This paper, based on the classical infectious disease model, considers the effects of social reinforcement and the neutral attitudes of netizens on information dissemination. A two-stage evolution model of public opinion reversal in online networks is established, and the model is simulated using a BA scale-free network. The simulation study analyzes the impact of the presence of neutrals and social reinforcement on the evolution of public opinion. The simulation results validate the effectiveness of the established model, providing a new theoretical perspective for the study of the evolution of public opinion reversal in online networks. It also offers some reference ideas for the government to better manage cyberspace.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jianhua Dai
AU  - Yuanyuan Ma
PY  - 2024
DA  - 2024/11/13
TI  - Construction of a Network Public Opinion Reversal Dissemination Model Considering the Role of Social Reinforcement
BT  - Proceedings of the 2024 5th International Conference on Big Data and Social Sciences (ICBDSS 2024)
PB  - Atlantis Press
SP  - 308
EP  - 319
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-562-1_29
DO  - 10.2991/978-94-6463-562-1_29
ID  - Dai2024
ER  -