发表机构
Mälardalen University; Stockholm University; Institute for Futures Studies（马尔默达伦大学; 斯德哥尔摩大学; 未来研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出非线性两群体平均场模型，区分个体过滤、同质性和接收端定制三条极化路径，并揭示反馈进入位置对集体极化的关键影响。
AI 中文摘要
集体极化可以通过作用于社会沟通不同阶段的机制产生，但相似的极化结果并不必然意味着动态上等价的过程。我们引入了一个非线性两群体平均场模型，该模型区分了三条通向极化的路径：个体内容过滤、同质性（选型配对）和接收端消息定制。发送端重构被纳入作为补充的中介过程，它在源信号混合之前对其进行转换。这些消息转换的动机源于人工智能介导的文化传播，其中中介者可以重构消息或使其适应接收者。利用共同坐标和差异坐标，我们推导出朝向共识和平衡极化的不稳定性的通用条件，并在完整的二维相平面中分析所得的稳态分支。个体过滤可以通过状态依赖的更新产生极化，同质性可以在社会场中保持群体差异，而接收端定制即使在完全混合的情况下也能产生极化反馈。相比之下，发送端重构仅在同质性保持差异化源信号时影响极化模式。尽管这些机制可以产生相同的局部不稳定性条件或平衡分支幅度，但它们通过横向稳定性、非对称均衡、多稳态和盆地几何形状仍然可区分。特别是，平衡极化可能先作为鞍点出现，然后成为稳定吸引子，而非对称鞍点组织了共识盆地和极化盆地之间的边界。这些结果表明，集体极化不仅取决于反馈强度，还取决于反馈进入沟通过程的位置。
英文摘要
Collective polarization can arise through mechanisms acting at different stages of social communication, but similar polarized outcomes need not imply dynamically equivalent processes. We introduce a nonlinear two-group mean-field model that distinguishes three routes to polarization: individual content filtering, assortativity, and receiver-side message tailoring. Sender-side reformulation is included as a complementary mediation process that transforms source signals before they are mixed. These message transformations are motivated by AI-mediated cultural transmission, in which intermediaries can reformulate messages or adapt them to receivers. Using common and difference coordinates, we derive general conditions for instabilities toward consensus and balanced polarization and analyze the resulting stationary branches in the full two-dimensional phase plane. Individual filtering can generate polarization through state-dependent updating, assortativity can preserve group differences in the social field, and receiver tailoring can create a polarizing feedback even under complete mixing. By contrast, sender-side reformulation affects the polarization mode only when assortativity preserves differentiated source signals. Although these mechanisms can produce identical local instability conditions or balanced-branch amplitudes, they remain distinguishable through transverse stability, asymmetric equilibria, multistability, and basin geometry. In particular, balanced polarization may emerge as a saddle before becoming a stable attractor, while asymmetric saddles organize the boundary between consensus and polarization basins. These results show that collective polarization depends not only on feedback strength, but also on where feedback enters the communication process.
Comments17 pages, 6 figures
