对人类动力学的理解
Towards the understanding of human dynamics
摘要：
对人类行为的定量理解提供了对许多人类启动系统的复杂性的基本理解。在以前的人类动力学分析中嵌入的一个基本假设是，它的时间统计是均匀和平稳的，这可以适当地描述为泊松过程。因此，间隔时间分布应该具有指数尾部。然而，最近，这一假设受到了广泛的证据的挑战，从通信到娱乐和工作模式，人类动力学服从非泊松统计与重尾间隔时间分布。本文综述了近年来对人类活动模式的实证研究，以及任务驱动和兴趣驱动系统的理论模型。最后，我们概述了人类动力学统计力学研究中的一些未来的开放性问题。
英文摘要：
Quantitative understanding of human behaviors provides elementary comprehension of the complexity of many human-initiated systems. A basic assumption embedded in the previous analyses on human dynamics is that its temporal statistics are uniform and stationary, which can be properly described by a Poisson process. Accordingly, the interevent time distribution should have an exponential tail. However, recently, this assumption is challenged by the extensive evidence, ranging from communication to entertainment and work patterns, that the human dynamics obeys non-Poisson statistics with heavy-tailed interevent time distribution. This review article summarizes the recent empirical explorations on human activity pattern, as well as the corresponding theoretical models for both task-driven and interest-driven systems. Finally, we outline some future open questions in the studies of the statistical mechanics of human dynamics.
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