Regret Psychology-Driven Information Propagation and Behavioral Adoption in Complex Social Networks

In recent years, information propagation on social networks has attracted extensive attention, with psychological characteristics of individuals exerting a significant influence on the diffusion process. Our study investigates the role of regret psychology and its impact on information spreading and behavioral adoption. We categorize individuals into regretful and non-regretful groups and introduce regret intensity together with the proportion of regretful individuals as dynamic variables. Based on this, we construct a two-layer interactive model consisting of a psychological layer and a behavioral layer. Then we establish the behavioral adoption model for the heterogeneous population and study the propagation characteristics of the regretful individuals on social networks. Furthermore, we derive the propagation dynamics using edge-based compartmental theory to examine the transmission mechanism. Numerical simulations, which coincide nicely with our theoretical analyses, reveal the crossover phenomena in phase transitions: as the regret threshold increases, adoption dynamics shift from second-order continuous to first-order discontinuous transitions. More importantly, for a given propagation probability, there exists an optimal regret threshold that maximizes the final adoption size. These findings highlight the crucial role of regret psychology in reshaping the propagation mechanism and provide a new theoretical perspective for understanding symmetry transformations and group heterogeneity in social contagion dynamics.

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Publication Details

Journal
Symmetry
Published
2025-11-20
DOI
https://doi.org/10.3390/sym17112008
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00

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article

Regret Psychology-Driven Information Propagation and Behavioral Adoption in Complex Social Networks

Chenxi Hu, Nana Li, Yang Tian, Xuzhen Zhu et al.
Symmetry
Opinion Dynamics and Social Influence
article

Regret Psychology-Driven Information Propagation and Behavioral Adoption in Complex Social Networks

Chenxi Hu, Nana Li, Yang Tian, Xuzhen Zhu, Yajuan Cui, Simin Hu
article en

Abstract

In recent years, information propagation on social networks has attracted extensive attention, with psychological characteristics of individuals exerting a significant influence on the diffusion process. Our study investigates the role of regret psychology and its impact on information spreading and behavioral adoption. We categorize individuals into regretful and non-regretful groups and introduce regret intensity together with the proportion of regretful individuals as dynamic variables. Based on this, we construct a two-layer interactive model consisting of a psychological layer and a behavioral layer. Then we establish the behavioral adoption model for the heterogeneous population and study the propagation characteristics of the regretful individuals on social networks. Furthermore, we derive the propagation dynamics using edge-based compartmental theory to examine the transmission mechanism. Numerical simulations, which coincide nicely with our theoretical analyses, reveal the crossover phenomena in phase transitions: as the regret threshold increases, adoption dynamics shift from second-order continuous to first-order discontinuous transitions. More importantly, for a given propagation probability, there exists an optimal regret threshold that maximizes the final adoption size. These findings highlight the crucial role of regret psychology in reshaping the propagation mechanism and provide a new theoretical perspective for understanding symmetry transformations and group heterogeneity in social contagion dynamics.

SymmetryVol. 17(11)
Beijing University of Posts and Telecommunications (CN), Zhengzhou University of Light Industry (CN), Beijing Information Science & Technology University (CN)
Zhengzhou University of Light Industry, Zhengzhou University, Henan Provincial Science and Technology Research Project
Openalex Percentile: Top 72%
Opinion Dynamics and Social Influence
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