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Mitigating opinion polarization in social networks using adversarial attacks.
Michinori Ninomiya1, Genki Ichinose2, Katsumi Chiyomaru3
1Department of Mathematical and Systems Engineering, Shizuoka University, Hamamatsu, 432-8561, Japan.
Scientific Reports
|March 17, 2025
Summary
This study shows that strategically adding perturbations to social network links can mitigate opinion polarization. This method is more effective in larger networks, offering a way to prevent division in online communities.
Area of Science:
- Computational Social Science
- Network Science
- Opinion Dynamics
Background:
- Social networking services (SNS) facilitate connections among like-minded individuals.
- This can lead to decreased exposure to diverse viewpoints and increased opinion polarization.
- Existing research has explored conditions for polarization but lacked mitigation strategies.
Purpose of the Study:
- To investigate the potential of artificial perturbations to mitigate opinion polarization in network models.
- To determine if adversarial-inspired perturbations can reverse or reduce opinion divergence.
Main Methods:
- Conducted numerical simulations of opinion dynamics models.
- Introduced strategic perturbations to the weights of network links.
- Analyzed the impact of perturbation strength and network size on polarization.
Main Results:
- Opinion polarization can be effectively mitigated by strategically perturbing network link weights.
- The degree of mitigation increases with the strength of the applied perturbations.
- The proposed method for mitigating polarization is more effective in larger network structures.
Conclusions:
- Strategic perturbation of network links offers a viable method to counteract opinion polarization.
- This approach shows promise for fostering more diverse opinion landscapes in online social networks.
- The effectiveness scales with network size, suggesting applicability to large-scale platforms.
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