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<p>In social networks, users’ opinions on specific events often exhibit diversity, leading to phenomena of segmentation or audience differentiation, where users with similar opinions tend to cluster into network circles. To gain a deeper understanding of this phenomenon and the underlying dynamics of dissemination, this study constructs the I2EH2S2R model, which considers opinion divergence based on homogeneous networks. This model innovatively introduces three types of nodes that have received information but have not yet disseminated it: exposed node 1, exposed node 2, and hesitation node, to more precisely characterize the behavioral differences of users in the information dissemination process. In the design of the model mechanism, we particularly focus on the conversion process of the two types of exposed nodes into hesitation nodes. By quantifying the competitive relationship between the two opinions, we reveal the dynamic characteristics of information dissemination. Considering the practical situation where some silent nodes may transform into disseminating nodes upon receiving information again, we establish a secondary dissemination mechanism to more accurately simulate the information dissemination process in real social networks.Through steady-state analysis of the model for single and multiple opinions, we derive the corresponding threshold conditions, providing a theoretical basis for understanding the dynamic characteristics of information dissemination. Numerical simulation results show that the user disengagement rate primarily affects the scale of information dissemination, while its impact on the peak time of dissemination node density is not significant. At the same time, the user silence rate has a significant impact on the scale of information dissemination, indicating that guiding users’ willingness to disseminate information can more effectively control the direction of public opinion. Additionally, the secondary dissemination mechanism significantly promotes the dissemination of both opinions.</p>

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Dynamical analysis of an I2EH2S2R information spreading model with opinion divergence

  • 期刊论文

  • 发表日期：

    2025年1月28日

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  • Yan Wang,
  • Mingyu Cui,
  • Ming Liu,
  • Chuanbiao Wang,
  • Quan Wang

摘要

In social networks, users’ opinions on specific events often exhibit diversity, leading to phenomena of segmentation or audience differentiation, where users with similar opinions tend to cluster into network circles. To gain a deeper understanding of this phenomenon and the underlying dynamics of dissemination, this study constructs the I2EH2S2R model, which considers opinion divergence based on homogeneous networks. This model innovatively introduces three types of nodes that have received information but have not yet disseminated it: exposed node 1, exposed node 2, and hesitation node, to more precisely characterize the behavioral differences of users in the information dissemination process. In the design of the model mechanism, we particularly focus on the conversion process of the two types of exposed nodes into hesitation nodes. By quantifying the competitive relationship between the two opinions, we reveal the dynamic characteristics of information dissemination. Considering the practical situation where some silent nodes may transform into disseminating nodes upon receiving information again, we establish a secondary dissemination mechanism to more accurately simulate the information dissemination process in real social networks.Through steady-state analysis of the model for single and multiple opinions, we derive the corresponding threshold conditions, providing a theoretical basis for understanding the dynamic characteristics of information dissemination. Numerical simulation results show that the user disengagement rate primarily affects the scale of information dissemination, while its impact on the peak time of dissemination node density is not significant. At the same time, the user silence rate has a significant impact on the scale of information dissemination, indicating that guiding users’ willingness to disseminate information can more effectively control the direction of public opinion. Additionally, the secondary dissemination mechanism significantly promotes the dissemination of both opinions.