人类动力学中具有重尾的理性偏差的量化
Quantification of deviations from rationality with heavy-tails in human dynamics
摘要：
技术、经济和社会现象的动态是由人类如何组织他们的日常工作以应对内源性和外源性刺激来控制的。假设理论被认为提供了一个通用的答案来解释经常观察到的任务完成前等待时间的幂律分布。然而，权力法的普遍有效性和其他制度的性质仍然悬而未决。使用谷歌在万维网层面收集的匿名数据，我们确定了几个额外的制度的存在，这些制度表征了互联网用户在收到消息后执行给定任务所需的时间。根据下或过度利用时间的人口的用户和他们的响应扰动的强度，纯幂律被发现是coextensive与指数制度（任务执行没有太多的延迟）和交叉到渐近高原（一些任务从来没有执行）。我们的研究揭示了人类行为的可用性和效率的特征，这对理解人类决策、互联网安全等政策的最佳设计、集体行为的溢出效应、群体动态和社会流行病具有重要意义。
英文摘要：
The dynamics of technological, economic and social phenomena is controlled by how humans organize their daily tasks in response to both endogenous and exogenous stimulations. Queueing theory is believed to provide a generic answer to account for the often observed power-law distributions of waiting times before a task is fulfilled. However, the general validity of the power law and the nature of other regimes remain unsettled. Using anonymized data collected by Google at the World Wide Web level, we identify the existence of several additional regimes characterizing the time required for a population of Internet users to execute a given task after receiving a message. Depending on the under- or over-utilization of time by the population of users and the strength of their response to perturbations, the pure power law is found to be coextensive with an exponential regime (tasks are performed without too much delay) and with a crossover to an asymptotic plateau (some tasks are never performed). The characterization of the availability and efficiency of humans on their actions revealed by our study have important consequences to understand human decision-making, optimal designs of policies such as for Internet security, with spillovers to collective behaviors, crowds dynamics, and social epidemics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
