The origin of bursts and heavy tails in human dynamics
The origin of bursts and heavy tails in human dynamics
复制标题
DOI：
10.1038/nature03459
复制
发表时间：
2005-05-12
期刊：
影响因子：
64.8
通讯作者：
Barabási, AL
中科院分区：
文献类型：
--
作者：
Barabási, AL
许多社会、技术和经济现象的动态都是由人类个体行为驱动的，这使得对人类行为的定量理解成为现代科学的核心问题。当前从风险评估到通信的人类动力学模型都假设人类行为在时间上随机分布，因此可以很好地近似于泊松过程 (1-3)。相比之下，越来越多的证据表明，从交流到娱乐和工作模式等许多人类活动的时间安排都遵循非泊松统计，其特点是快速发生的事件爆发，中间间隔很长一段时间不活动(4-8)。在这里，我表明人类行为的突发性是基于决策的排队过程的结果（9,10）：当个人根据某些感知的优先级执行任务时，任务的时间安排将是重尾的，大多数任务会快速执行，而少数任务会经历很长的等待时间。相反，随机或优先级盲执行可以通过统一的事件间统计数据很好地近似。这些发现对通信和零售业从资源管理到服务分配都有重要影响。
The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behaviour into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes(1-3). In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity(4-8). Here I show that the bursty nature of human behaviour is a consequence of a decision-based queuing process(9,10): when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times. In contrast, random or priority blind execution is well approximated by uniform inter-event statistics. These finding have important implications, ranging from resource management to service allocation, in both communications and retail.