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Strategies for reducing polarization in social networks

Author

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  • Wu, Yue
  • Li, Linjiao
  • Yu, Qiannan
  • Gan, Jiaxin
  • Zhang, Yi

Abstract

The widespread usage of social networks has intensified the phenomenon of opinion polarization. This polarization has a corrosive effect on the functioning of public opinions, societies, and democracies. Hence, it is vital to devise strategies for reducing polarization. In this paper, we propose a depolarization model based on the modified linear threshold model and the Hegselmann-Krause model. Using this model, we then devise three depolarization strategies (building heterogeneous edges, embedding local neutral opinion, and introducing global neutral opinion), and conduct depolarization experiments with varied parameters, including self-belief parameter, social influence moderating parameter, and the selection mode of new edges and active nodes. Our experiments with synthesized and real-world datasets have yielded some interesting results.

Suggested Citation

  • Wu, Yue & Li, Linjiao & Yu, Qiannan & Gan, Jiaxin & Zhang, Yi, 2023. "Strategies for reducing polarization in social networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    • Handle: RePEc:eee:chsofr:v:167:y:2023:i:c:s0960077922012747
    DOI: 10.1016/j.chaos.2022.113095
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    References listed on IDEAS

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    Cited by:

    1. Liman Du & Wenguo Yang & Suixiang Gao, 2024. "Maximizing diversity and persuasiveness of opinion articles in social networks," Journal of Combinatorial Optimization, Springer, vol. 48(5), pages 1-44, December.
    2. Ding, Haixin & Xie, Li, 2024. "The applicability of positive information in negative opinion management: An attitude-laden communication perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 645(C).

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