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Social contagions with information sensitivity in complex networks

Author

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  • Xing-Li Jing

    (Jiyuan Vocational and Technical College)

  • Ming Tang

    (East China Normal University)

  • Ying Liu

    (Southwest Petroleum University)

Abstract

The behavior adoption is a complex social contagion process where non-redundancy and social reinforcement are at work in the transmission of behavioral information. While individual’s attitude toward the behavior information remarkably affects the behavior spreading dynamics in real world, its influence in social contagions has not been fully explored. To this end, we propose a behavior information spreading model with both information sensitivity and social reinforcement, where the information sensitivity represents the degree to which an individual is interested in the behavior. In the process of information spreading, whether an individual accepts or adopts a behavior is affected by the information transmission rate, information sensitivity and social reinforcement. To understand the contagion dynamics of this model, we develop a heterogeneous edge-based compartmental theory. We find that the acceleration of the rate of behavior adoption and the improvement of the scope of behavior adoption can be achieved by increasing either the information transmission rate, information sensitivity or social reinforcement. In ER networks, by changing the values of transmission rate, information sensitivity and social reinforcement, the type of phase transition of the final adopted size can be transformed between continuous and discontinuous. In BA networks, under different values of transmission rate, information sensitivity and social reinforcement, the final adopted size is continuously increasing. Graphical Abstract The dependence of the final fraction of adopted individuals on both transmission rate and social reinforcement

Suggested Citation

  • Xing-Li Jing & Ming Tang & Ying Liu, 2024. "Social contagions with information sensitivity in complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(4), pages 1-9, April.
  • Handle: RePEc:spr:eurphb:v:97:y:2024:i:4:d:10.1140_epjb_s10051-024-00668-6
    DOI: 10.1140/epjb/s10051-024-00668-6
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    References listed on IDEAS

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    1. Vincenza Carchiolo & Alessandro Longheu & Michele Malgeri & Giuseppe Mangioni & Marialaura Previti, 2021. "Mutual Influence of Users Credibility and News Spreading in Online Social Networks," Future Internet, MDPI, vol. 13(5), pages 1-15, April.
    2. Ruan, Zhongyuan & Zhang, Lina & Shu, Xincheng & Xuan, Qi, 2022. "Social contagion with negative feedbacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    3. Wang, Wei & Chen, Xiao-Long & Zhong, Lin-Feng, 2018. "Social contagions with heterogeneous credibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 604-610.
    4. Peng, Hao & Peng, Wangxin & Zhao, Dandan & Wang, Wei, 2020. "Impact of the heterogeneity of adoption thresholds on behavior spreading in complex networks," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    5. Yining Xu & Jinghua Xiao & Xiaochen Wang & Yuexia Zhang, 2022. "Effect of Contact Preference among Heterogeneous Individuals on Social Contagions," Complexity, Hindawi, vol. 2022, pages 1-15, January.
    6. Li, Weihua & Tang, Shaoting & Pei, Sen & Yan, Shu & Jiang, Shijin & Teng, Xian & Zheng, Zhiming, 2014. "The rumor diffusion process with emerging independent spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 121-128.
    7. Wang, Jiajia & Zhao, Laijun & Huang, Rongbing, 2014. "SIRaRu rumor spreading model in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 43-55.
    8. Leng, Hui & Zhao, Yi & Wang, Dong, 2022. "Message passing approach for social contagions based on the trust probability with multiple influence factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
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