Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process
Currently, China is in the period of social transformation. Such transformation continuously results in high group polarization behaviors, which attracts many attentions. In order to explore the evolutionary mechanism and formation process of group polarization behavior, this paper proposes a group...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/4791527 |
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| _version_ | 1832555076571365376 |
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| author | Tinggui Chen Jiawen Shi Jianjun Yang Guodong Cong Gongfa Li |
| author_facet | Tinggui Chen Jiawen Shi Jianjun Yang Guodong Cong Gongfa Li |
| author_sort | Tinggui Chen |
| collection | DOAJ |
| description | Currently, China is in the period of social transformation. Such transformation continuously results in high group polarization behaviors, which attracts many attentions. In order to explore the evolutionary mechanism and formation process of group polarization behavior, this paper proposes a group polarization model which is integrated into the Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model. In this paper, firstly, the SIRS epidemic model and the factors of relationship strength are introduced based on the J-A model (proposed by Jager and Amblard) to enhance the information transmission and interaction among individuals. In addition, the BA network (proposed by Barabasi and Albert) model is used as the agent adjacency model due to its closeness to the real social network structure. After that, the Monte Carlo method is applied to conduct experimental simulation. Subsequently, this paper analyzes the simulation results in threefold: (1) comparison of polarization processes with and without integration of the SIRS epidemic model; (2) adjusting the immune recovery parameter γ and the relationship strength z to explore the role of these two parameters in the polarization process; and (3) comparing the polarization effects of different network structures. Through the experiments, we find that BA network is more polarized than small-world network in the same scale. Finally, corresponding measures are proposed to prevent and mitigate the occurrence of group polarization. |
| format | Article |
| id | doaj-art-d0df0a23e7e8450e8eb7ffa83fd5811e |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-d0df0a23e7e8450e8eb7ffa83fd5811e2025-02-03T05:49:38ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/47915274791527Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion ProcessTinggui Chen0Jiawen Shi1Jianjun Yang2Guodong Cong3Gongfa Li4School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, ChinaBusiness and Tourism Institute, Hangzhou Vocational and Technical College, Hangzhou, ChinaDepartment of Computer Science and Information Systems, University of North Georgia, Oakwood, GA, USASchool of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou, ChinaHubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, ChinaCurrently, China is in the period of social transformation. Such transformation continuously results in high group polarization behaviors, which attracts many attentions. In order to explore the evolutionary mechanism and formation process of group polarization behavior, this paper proposes a group polarization model which is integrated into the Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model. In this paper, firstly, the SIRS epidemic model and the factors of relationship strength are introduced based on the J-A model (proposed by Jager and Amblard) to enhance the information transmission and interaction among individuals. In addition, the BA network (proposed by Barabasi and Albert) model is used as the agent adjacency model due to its closeness to the real social network structure. After that, the Monte Carlo method is applied to conduct experimental simulation. Subsequently, this paper analyzes the simulation results in threefold: (1) comparison of polarization processes with and without integration of the SIRS epidemic model; (2) adjusting the immune recovery parameter γ and the relationship strength z to explore the role of these two parameters in the polarization process; and (3) comparing the polarization effects of different network structures. Through the experiments, we find that BA network is more polarized than small-world network in the same scale. Finally, corresponding measures are proposed to prevent and mitigate the occurrence of group polarization.http://dx.doi.org/10.1155/2020/4791527 |
| spellingShingle | Tinggui Chen Jiawen Shi Jianjun Yang Guodong Cong Gongfa Li Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process Complexity |
| title | Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process |
| title_full | Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process |
| title_fullStr | Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process |
| title_full_unstemmed | Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process |
| title_short | Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Process |
| title_sort | modeling public opinion polarization in group behavior by integrating sirs based information diffusion process |
| url | http://dx.doi.org/10.1155/2020/4791527 |
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