认知网络、集体误解与社会知识的操纵
Epistemic Networks, Collective Misperception, and the Manipulation of Social Knowledge
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中文总结 AI 辅助
该研究聚焦网络中智能体的交互信念结构，提出以相互归因张量为社会认知分析单元，揭示集体误解等现象的构成及高阶信念与认知网络游走的关联。
中文摘要 AI 辅助
我们研究网络中交互信念的结构：即智能体持有、修正并基于其对其他智能体认知状态的模型采取行动的认知状态。群体的信念取决于每个成员智能体认为其他智能体相信的内容，以及每个智能体认为其他智能体对其余智能体的信念。我们提出，社会认知分析的恰当单元不是个体信念，而是相互归因的张量，即记录每个智能体认为每个其他智能体相信内容的数组。我们将该对象分为三层：私人持有的内容、公开表达的内容，以及他人应相信的内容。社会信念通过该张量与认知影响符号矩阵的收缩而演化。集体误解可精确分解为观察可消除的部分和观察无法触及的部分。社会从众会放大多元无知但不会产生它。集体认知共识、极化、根深蒂固的误解和不稳定的稳定形式是单一算子的谱域。在明确的认知一致性假设下，高阶信念可简化为认知网络中的游走，我们精确标记了该假设的边界。
英文摘要
We investigate the structure of interactive beliefs in networks: the epistemic state in which agents hold, revise, and act on their models of the epistemic states of other agents. What a group believes depends on what each member agent takes the others to believe, and on what each takes the others to believe about still others. We posit that the proper unit of social-epistemic analysis is not the individual belief but the tensor of mutual attribution, the array that records what every agent takes every agent to believe. We separate three layers of this object: what is privately held, what is publicly expressed, and what is to be believed by others. Social belief evolves by contraction of the tensor against a signed matrix of epistemic influence. Collective misperception decomposes exactly into a component that observation dissolves and a component that observation cannot touch. Social conformity amplifies pluralistic ignorance without generating it. The stable forms of collective epistemic consensus, polarization, entrenched misperception, and instability are spectral regimes of a single operator. Higher-order belief reduces to walks in the epistemic network, under a stated assumption of cognitive consistency whose boundary we mark precisely.
