爆炸性的意见极化和脱极化与不对称的感知
Haoyang Qian1, Malbor Asllani1
1Florida State University, Department of Mathematics, 1017 Academic Way, Tallahassee, Florida 32306, USA.
Physical review. E
|November 18, 2025
概括
在社交网络中,不对称的意见感知会导致爆炸性的两极分化和突然的脱极化. 了解这些非线性动态对于制定减轻社会分裂的战略至关重要.
科学领域:
- 社会物理学的社会物理.
- 计算社会科学 计算社会科学
- 网络科学 网络科学
背景情况:
- 社会上的分歧体现在经济,政治,宗教和意识形态的各个方面.
- 了解极化机制对于开发去极化策略至关重要.
研究的目的:
- 研究如何不对称的意见感知影响结构化社区的极化和脱极化.
- 分析非线性发病率术语和社交网络模块化在意见动态中的作用.
主要方法:
- 使用非线性发病率术语建模不对称的意见感知.
- 利用模块化社交网络结构和相邻矩阵自向量.
- 开发一个平均场近似来分析相位过渡和分叉.
主要成果:
- 不对称的感知导致爆炸性的两极分化和歇斯底里驱动的突然脱极化.
- 非线性发病率术语导致第一阶段过渡和特定的分叉行为.
- 意见两极分化模式与社交网络社区和过渡动态有关.
结论:
- 不对称的意见感知是极化和脱极化动态的关键驱动力.
- 这项研究提供了一个理论框架,用于理解结构化人口中的观点转变.
- 调查结果提供了通过基于网络的策略来缓解社会分裂的见解.
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