Generalized reciprocity -- the tendency to help others after receiving help oneself -- is widely theorized as a mechanism sustaining cooperation on online knowledge-sharing platforms. Yet robust empirical evidence from field settings remains surprisingly scarce. Prior studies relying on survey self-reports struggle to distinguish reciprocity from other prosocial motives, while observational designs confound reciprocity with baseline user activity, producing upward-biased estimates. We address these empirical challenges by developing a matched difference-in-differences survival analysis that leverages the temporal structure of help-seeking and help-giving on Stack Overflow. Using Cox proportional hazards models on over 21 million questions, we find that receiving an answer significantly increases a user's propensity to help others, but this effect is concentrated among newcomers and declines with platform experience. This pattern suggests that reciprocity functions primarily as a contributor-recruitment mechanism, operating before platform-specific incentives such as reputation and status displace the general moral impulse to reciprocate. Response time moderates the effect, but non-linearly: reciprocity peaks for answers arriving within a re-engagement window of roughly thirty to sixty minutes. These findings contribute to the theory of generalized reciprocity and have implications for platform design.

翻译：广义互惠——即个体在获得帮助后倾向于帮助他人的机制——被广泛理论化为在线知识共享平台维持合作的重要机制。然而，来自实地环境的稳健实证证据却出乎意料地稀少。以往依赖调查自述报告的研究难以将互惠与其他亲社会动机区分开来，而观测性设计则将互惠与用户基线活动混淆，导致估计值向上偏差。为应对这些实证挑战，我们开发了一种匹配双重差分生存分析方法，利用Stack Overflow上求助与助人的时间结构。基于超过2100万个问题的Cox比例风险模型，我们发现收到答案会显著提高用户帮助他人的倾向，但这种效应集中于新手用户，并随平台经验增加而减弱。这一模式表明，互惠主要作为一种贡献者招募机制发挥作用，在平台特定激励（如声誉和地位）取代一般道德冲动之前运作。响应时间对效应具有调节作用，但呈非线性：当答案在约30至60分钟的重新参与窗口内到达时，互惠效应达到峰值。这些发现为广义互惠理论做出了贡献，并对平台设计具有启示意义。