Center for Complex Network Research, Department of Physics, Northeastern University, Boston, MA 02115, USA.
Science. 2010 Feb 19;327(5968):1018-21. doi: 10.1126/science.1177170.
A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to foresee the whereabouts and mobility of individuals, raising a fundamental question: To what degree is human behavior predictable? Here we explore the limits of predictability in human dynamics by studying the mobility patterns of anonymized mobile phone users. By measuring the entropy of each individual's trajectory, we find a 93% potential predictability in user mobility across the whole user base. Despite the significant differences in the travel patterns, we find a remarkable lack of variability in predictability, which is largely independent of the distance users cover on a regular basis.
从预测人类和电子病毒的传播,到城市规划和移动通信中的资源管理,各种应用都依赖于我们预测个人行踪和移动性的能力,这引发了一个基本问题:人类行为在多大程度上是可预测的?在这里,我们通过研究匿名手机用户的移动模式来探索人类动态可预测性的极限。通过测量每个人轨迹的熵,我们发现整个用户群体的用户移动性具有 93%的潜在可预测性。尽管旅行模式存在显著差异,但我们发现可预测性的变化非常小,而且在很大程度上与用户日常覆盖的距离无关。