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Coupled dynamics of information propagation and emotion influence: Emerging emotion clusters for public health emergency messages on the Chinese Sina Microblog

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Listed:
  • Yin, Fulian
  • Tang, Xinyi
  • Liang, Tongyu
  • Kuang, Qinghua
  • Wang, Jinxia
  • Ma, Rui
  • Miao, Fang
  • Wu, Jianhong

Abstract

A major distinction between the COVID-19 pandemic and previous pandemics is the significant role of social media platforms in shaping public adherence to non-pharmaceutical interventions and vaccine acceptance. The information propagation and individual emotion communication relevant to public health messages have been promoted in the Chinese Sina Microblog, one of the most popular social platforms in China, through two major interaction mechanisms, “commenting” and “forwarding”. Here, we develop a hybrid system of macro information propagation dynamics Susceptible-Commenting-Forwarding-Immune model coupled with the micro emotion influence dynamics Hegselmann-Krause model, termed HK-SCFI coupled system, and reveal the mechanisms of individual emotion infection using the commenting and forwarding data (including time point and content) publicly available on public opinion events in the Chinese Sina Microblog. We demonstrate how our data-driven and model-informed analysis can provide quantitative insights into the co-evolution mechanism of individual emotion during information propagation, describe the emergency of emotion clusters, and predict individual emotion evolution trends. Our study shows that multiple interactive mechanisms can facilitate the propagation of public messages and shape public sentiment through online social networks. Our modeling framework can potentially be a tool for designing effective propagation strategies during public health emergencies.

Suggested Citation

  • Yin, Fulian & Tang, Xinyi & Liang, Tongyu & Kuang, Qinghua & Wang, Jinxia & Ma, Rui & Miao, Fang & Wu, Jianhong, 2024. "Coupled dynamics of information propagation and emotion influence: Emerging emotion clusters for public health emergency messages on the Chinese Sina Microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    • Handle: RePEc:eee:phsmap:v:639:y:2024:i:c:s0378437124001389
    DOI: 10.1016/j.physa.2024.129630
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    1. Kumar, Ajay & Swarnakar, Pradip & Jaiswal, Kamya & Kurele, Ritika, 2020. "SMIR model for controlling the spread of information in social networking sites," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    2. Hui Xie & Guangjian Li & Yongjie Yan & Sihui Shu, 2017. "Evolution of Bounded Confidence Opinion in Social Networks," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-5, April.
    3. Fu, Guiyuan & Zhang, Weidong & Li, Zhijun, 2015. "Opinion dynamics of modified Hegselmann–Krause model in a group-based population with heterogeneous bounded confidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 558-565.
    4. Huo, Liang’an & Cheng, Yingying, 2019. "Dynamical analysis of a IWSR rumor spreading model with considering the self-growth mechanism and indiscernible degree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    5. Ume L Abbas & Roy M Anderson & John W Mellors, 2007. "Potential Impact of Antiretroviral Chemoprophylaxis on HIV-1 Transmission in Resource-Limited Settings," PLOS ONE, Public Library of Science, vol. 2(9), pages 1-11, September.
    6. Cheng, Chun & Yu, Changbin, 2019. "Opinion dynamics with bounded confidence and group pressure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    7. Yin, Fulian & Xia, Xinyu & Zhang, Xiaojian & Zhang, Mingjia & Lv, Jiahui & Wu, Jianhong, 2021. "Modelling the dynamic emotional information propagation and guiding the public sentiment in the Chinese Sina-microblog," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    8. Fu, Minglei & Feng, Jun & Lande, Dmytro & Dmytrenko, Oleh & Manko, Dmytro & Prakapovich, Ryhor, 2021. "Dynamic model with super spreaders and lurker users for preferential information propagation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    9. Decui Liang & Bochun Yi & Zeshui Xu, 2021. "Opinion dynamics based on infectious disease transmission model in the non-connected context of Pythagorean fuzzy trust relationship," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(12), pages 2783-2803, December.
    10. Wander Jager & Frédéric Amblard, 2005. "Uniformity, Bipolarization and Pluriformity Captured as Generic Stylized Behavior with an Agent-Based Simulation Model of Attitude Change," Computational and Mathematical Organization Theory, Springer, vol. 10(4), pages 295-303, January.
    11. Zhao, Danling & Sun, Jianbin & Tan, Yuejin & Wu, Jianhong & Dou, Yajie, 2018. "An extended SEIR model considering homepage effect for the information propagation of online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1019-1031.
    Full references (including those not matched with items on IDEAS)

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