摘要
定量研究人类行为有助于理解社会经济系统复杂性的来源。经典的人类动力学分析中包含了一个潜在的假设,就是人类行为的时间性可以用一个泊松过程很好地描述,因此人类发出相继行为的间隔时间分布应该具有一个指数的尾部。最近,大量的实证分析显示,从通讯模式到在线娱乐,从金融活动到网页浏览,人类行为的间隔时间分布具有明显的胖尾性质,这些发现开辟了一个名为人类动力学的新领域。介绍该领域的一些基本概念并总结目前已知的实证分析结果。
Quantitative understanding of human behaviors provides elementary comprehension of the complexity of many human-initiated systems. A basic assumption embedded in the previous analysis 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 introduces the fundamental concepts of human dynamics and summarizes the recent progress of empirical explorations. Finally, we outline some future open questions in the empirical studies of human dynamics.
出处
《复杂系统与复杂性科学》
EI
CSCD
2008年第2期15-24,共10页
Complex Systems and Complexity Science
基金
973项目(2006CB705500)
国家自然科学基金重点项目(10635040)
中国科学院院长特别基金
国家自然科学基金面上项目(70571074)及(10472116)
国家自然科学基金委信息学部主任基金(60744003)
国家自然基金理论物理前沿项目(A0524701)
上海市重点学科建设资助项目(T0502)
上海市自然科学基金项目(06ZR14144)
关键词
人类动力学
非泊松统计特性
间隔时间分布
回复时间分布
human dynamics
non-Poisson statistics
interevent time distribution
response time distribution