算法驱动的信息相似性与集体行动：一项实验研究

中文摘要 AI 辅助

我们研究个体信息的相似性如何塑造集体行动。当人们利用社交媒体等共同信息源时，会对他人所见及所为更有信心，这有助于协调，但也会引发搭便车行为。我们通过内容审核实验表明，两种力量何者占优取决于集体目标的要求程度。我们改变小组成员信息的相似性，固定个体自身所学，并独立改变删除阈值。更相似的信息在所需举报少时有阻碍作用，在所需举报多时则有促进作用。这证实了信息相似性理论的核心比较静态。引出的信念追踪到对关键地位感知的反转，并记录了其系统性校准错误。只有在关键地位一致时，更多参与才会转化为更大的集体成功和更高的福利。

英文摘要

We study how the similarity of individuals' information shapes collective action. When people draw on a common source of information, such as social media, each becomes more confident about what others have seen and will do. This can help them coordinate, but it can also tempt them to free-ride. We show that which force prevails depends on how demanding the collective goal is. In a content-moderation experiment, subjects decide whether to pay a cost to report harmful content, which is removed only if enough reports are received. We vary the similarity of group members' information, holding fixed what each learns on her own, and independently vary the removal threshold. More similar information impedes reporting when few reports suffice and facilitates it when many are required, lowering reporting by 17 percentage points under an easy threshold and raising it by 34 points under a demanding one. This confirms the central comparative static of the theory of information similarity (Basak, Deb and Kuvalekar, 2026). Elicited beliefs trace the reversal to perceived pivotality and document systematic miscalibration of it. Subjects overestimate pivotality across all regimes, and their beliefs respond to similarity in line with actual pivotality only at intermediate thresholds: easy thresholds produce unrecognized pivotality, and near-unanimous thresholds produce illusory pivotality. The two response-miscalibrated patterns coincide with welfare losses; only under aligned pivotality does greater participation translate into greater collective success and higher welfare.

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64 pages