Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks
In social network analysis, entropy quantifies the uncertainty or diversity of opinions, reflecting the complexity of opinion dynamics. To enhance the understanding of how opinions evolve, this study introduces a novel approach to modeling opinion dynamics in social networks by incorporating three-s...
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MDPI AG
2024-10-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/26/10/851 |
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| author | Haomin Wang Youyuan Li Jia Chen |
| author_facet | Haomin Wang Youyuan Li Jia Chen |
| author_sort | Haomin Wang |
| collection | DOAJ |
| description | In social network analysis, entropy quantifies the uncertainty or diversity of opinions, reflecting the complexity of opinion dynamics. To enhance the understanding of how opinions evolve, this study introduces a novel approach to modeling opinion dynamics in social networks by incorporating three-stage cascade information attenuation. Traditional models have often neglected the influence of second- and third-order neighbors and the attenuation of information as it propagates through a network. To correct this oversight, we redefine the interaction weights between individuals, taking into account the distance of opining, bounded confidence, and information attenuation. We propose two models of opinion dynamics using a three-stage cascade mechanism for information transmission, designed for environments with either a single or two subgroups of opinion leaders. These models capture the shifts in opinion distribution and entropy as information propagates and attenuates through the network. Through simulation experiments, we examine the ingredients influencing opinion dynamics. The results demonstrate that an increased presence of opinion leaders, coupled with a higher level of trust from their followers, significantly amplifies their influence. Furthermore, comparative experiments highlight the advantages of our proposed models, including rapid convergence, effective leadership influence, and robustness across different network structures. |
| format | Article |
| id | doaj-art-e16e668a7a6348ea8dccd25f638783be |
| institution | OA Journals |
| issn | 1099-4300 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-e16e668a7a6348ea8dccd25f638783be2025-08-20T02:11:00ZengMDPI AGEntropy1099-43002024-10-01261085110.3390/e26100851Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social NetworksHaomin Wang0Youyuan Li1Jia Chen2School of Management Science and Engineering, Southwestern University of Finance and Economics, Chengdu 610074, ChinaSchool of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, ChinaSchool of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, ChinaIn social network analysis, entropy quantifies the uncertainty or diversity of opinions, reflecting the complexity of opinion dynamics. To enhance the understanding of how opinions evolve, this study introduces a novel approach to modeling opinion dynamics in social networks by incorporating three-stage cascade information attenuation. Traditional models have often neglected the influence of second- and third-order neighbors and the attenuation of information as it propagates through a network. To correct this oversight, we redefine the interaction weights between individuals, taking into account the distance of opining, bounded confidence, and information attenuation. We propose two models of opinion dynamics using a three-stage cascade mechanism for information transmission, designed for environments with either a single or two subgroups of opinion leaders. These models capture the shifts in opinion distribution and entropy as information propagates and attenuates through the network. Through simulation experiments, we examine the ingredients influencing opinion dynamics. The results demonstrate that an increased presence of opinion leaders, coupled with a higher level of trust from their followers, significantly amplifies their influence. Furthermore, comparative experiments highlight the advantages of our proposed models, including rapid convergence, effective leadership influence, and robustness across different network structures.https://www.mdpi.com/1099-4300/26/10/851opinion dynamicsthree-stage cascadeinformation attenuationbounded confidence |
| spellingShingle | Haomin Wang Youyuan Li Jia Chen Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks Entropy opinion dynamics three-stage cascade information attenuation bounded confidence |
| title | Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks |
| title_full | Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks |
| title_fullStr | Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks |
| title_full_unstemmed | Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks |
| title_short | Three-Stage Cascade Information Attenuation for Opinion Dynamics in Social Networks |
| title_sort | three stage cascade information attenuation for opinion dynamics in social networks |
| topic | opinion dynamics three-stage cascade information attenuation bounded confidence |
| url | https://www.mdpi.com/1099-4300/26/10/851 |
| work_keys_str_mv | AT haominwang threestagecascadeinformationattenuationforopiniondynamicsinsocialnetworks AT youyuanli threestagecascadeinformationattenuationforopiniondynamicsinsocialnetworks AT jiachen threestagecascadeinformationattenuationforopiniondynamicsinsocialnetworks |