A public opinion propagation model for technological disasters

被引:0
|
作者
Zhang, Yi [1 ]
Tang, Wanjie [2 ]
Ni, Ting [3 ]
机构
[1] Sichuan Univ Sci & Engn, Management Sch, Zigong 643000, Peoples R China
[2] Sichuan Univ, West China Sch Publ Hlth, Chengdu 610064, Peoples R China
[3] Chengdu Univ Technol, Sch Environm & Civil Engn, Chengdu 610000, Peoples R China
来源
SCIENTIFIC REPORTS | 2025年 / 15卷 / 01期
基金
美国国家科学基金会;
关键词
SEIR MODEL; COVID-19; SPREAD;
D O I
10.1038/s41598-025-91244-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Public opinion on technological disasters is influenced by unique factors and characteristics. Based on the infectious disease model, this paper develops a public opinion dissemination model for technological disasters, considering factors such as disaster severity, government response, accountability, and the impact of both positive and negative media content. Using differential equation stability theory, we analyze the existence and stability of both the free propagation equilibrium point and the propagation equilibrium point. The next-generation matrix method is applied to calculate the propagation threshold, revealing that disaster severity, government response, and accountability are key factors in the spread of public opinion. Sensitivity analyses examine how these key factors affect public opinion dynamics. A case study on the Shiyan gas explosion in Hubei Province is presented, with microblog data used to calculate model parameters. The proposed public opinion dissemination model is applied to this case and compared with two other models, demonstrating the viability and effectiveness of the developed model. The analyses also show that well-handled government responses can help calm public opinion, even in cases where accountability is lacking. Finally, policy suggestions are offered to enhance public opinion management during technological disasters.
引用
收藏
页数:20
相关论文
共 50 条
  • [11] Semantic-based topic model for public opinion analysis in sudden-onset disasters
    Ma, Yulong
    Zhang, Xinsheng
    Wang, Runzhou
    APPLIED SOFT COMPUTING, 2025, 170
  • [12] Environmental disasters and public-opinion formation: A natural experiment
    Bohmelt, Tobias
    ENVIRONMENTAL RESEARCH COMMUNICATIONS, 2020, 2 (08):
  • [13] Stochastic Evolutionary Game Model of Hot Topics Propagation for Network Public Opinion
    Chen, Hongsong
    Zhao, Xiufeng
    IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2023, 11 (06) : 1 - 13
  • [14] The propagation behavior prediction of Tibetan network public opinion based on cloud model
    Li, Yingxing
    Li, Suduo
    2015 2ND INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING ICISCE 2015, 2015, : 994 - 997
  • [15] UAPE: Information Propagation Model Based on User Attitude and Public Opinion Environment
    Li, Xinyu
    Huang, Jinyang
    Zhang, Xiang
    Zhao, Peng
    Wang, Meng
    Zhuang, Guohang
    Yan, Huan
    Sun, Xiao
    Wang, Meng
    ICC 2024 - IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2024, : 13 - 18
  • [16] Network public opinion propagation model based on the influence of media and interpersonal communication
    Zhang, Yue-Xia
    Feng, Yi-Xuan
    Yang, Rui-Qi
    INTERNATIONAL JOURNAL OF MODERN PHYSICS B, 2019, 33 (32):
  • [17] Evolutionary Game Model of Public Opinion Information Propagation in Online Social Networks
    Wang, Jiakun
    Wang, Xinhua
    Fu, Li
    IEEE ACCESS, 2020, 8 : 127732 - 127747
  • [18] Study on Propagation Model of Network Public Opinion Based on Fuzzy Cellular Automata
    Ding Chunlong
    Wei Chaofan
    Gu Tingting
    Cul Caihao
    PROCEEDINGS OF 2013 2ND INTERNATIONAL CONFERENCE ON MEASUREMENT, INFORMATION AND CONTROL (ICMIC 2013), VOLS 1 & 2, 2013, : 1009 - 1013
  • [19] Modeling and Simulation Research on Propagation of Public Opinion
    Huang, Shiru
    Xiu, Baoxin
    Feng, Yanghe
    PROCEEDINGS OF 2016 IEEE ADVANCED INFORMATION MANAGEMENT, COMMUNICATES, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IMCEC 2016), 2016, : 380 - 384
  • [20] Two-Layer Coupled Network Model for Topic Derivation in Public Opinion Propagation
    Zhang, Yuexia
    Feng, Yixuan
    CHINA COMMUNICATIONS, 2020, 17 (03) : 176 - 187