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Dynamic immunization for disinformation spreading on signed social networks

Author

Listed:
  • Li, Ai-Wen
  • Liu, Ya-Fang
  • Zhou, Jian-Lin
  • Zeng, An
  • Xu, Xiao-Ke
  • Fan, Ying

Abstract

Signed social networks are a special type of social network with positive and negative relationships. It can provide a powerful framework for studying information spreading in light of opposite user relationships. Currently, static immunization strategies have been constructed to control the spread of disinformation on signed social networks. Here, we focus on dynamic immunization that can be real-time immune to the spread of disinformation on signed social networks, which is vital for shaping public discourse and opinion formation. Accordingly, we proposed the signed contact-tracing (SCT) considering the opposite attitudes of users toward information. Experiments with synthetic and empirical signed networks explore the impact of signed network structure with positive and negative edges on dynamic immunity and confirm the necessity of considering signs in the dynamic immune process. Then, the effectiveness of SCT was verified by two evaluation indicators, and find that targeting individuals with the same ideological group has a smaller spreading range and lower spreading speed than those without differentiated attitudes. Furthermore, the signed backward-contact-tracing (SBCT) based on SCT optimization offers optimal regulatory recommendations for enhancing immunity against disinformation in signed social networks. The study demonstrates how negative relationships impact the dynamic immunity of disinformation, and improves the application of dynamic immunity strategies in signed networks.

Suggested Citation

  • Li, Ai-Wen & Liu, Ya-Fang & Zhou, Jian-Lin & Zeng, An & Xu, Xiao-Ke & Fan, Ying, 2025. "Dynamic immunization for disinformation spreading on signed social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 659(C).
    • Handle: RePEc:eee:phsmap:v:659:y:2025:i:c:s0378437124008318
    DOI: 10.1016/j.physa.2024.130321
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    References listed on IDEAS

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