Temporal understanding of human mobility: A multi-time scale analysis

The recent availability of digital traces generated by cellphone calls has significantly increased the scientific understanding of human mobility. Until now, however, based on low time resolution measurements, previous works have ignored to study human mobility under various time scales due to sparse and irregular calls, particularly in the era of mobile Internet. In this paper, we introduced Mobile Flow Records, flow-level data access records of online activity of smartphone users, to explore human mobility. Mobile Flow Records collect high-resolution information of large populations. By exploiting this kind of data, we show the models and statistics of human mobility at a large-scale (3,542,235 individuals) and finer-granularity (7.5min). Next, we investigated statistical variations and biases of mobility models caused by different time scales (from 7.5min to 32h), and found that the time scale does influence the mobility model, which indicates a deep coupling of human mobility and time. We further show that mobility behaviors like transportation modes contribute to the diversity of human mobility, by exploring several novel and refined features (e.g., motion speed, duration, and trajectory distance). Particularly, we point out that 2-hour sampling adopted in previous works is insufficient to study detailed motion behaviors. Our work not only offers a macroscopic and microscopic view of spatial-temporal human mobility, but also applies previously unavailable features, both of which are beneficial to the studies on phenomena driven by human mobility.

近年来，手机通话产生的数字足迹的可获取性，显著提升了学界对人类移动性的科学认知水平。然而在此之前，由于依赖低时间分辨率的测量数据，且受限于稀疏且不规则的通话记录，既往研究未能针对不同时间尺度下的人类移动性展开系统探究——这一局限在移动互联网时代尤为凸显。为此，本文提出手机流量记录（Mobile Flow Records）：一类面向智能手机用户在线行为的流量级数据访问记录，用于人类移动性的相关研究。该数据集能够采集大规模人群的高分辨率移动信息。依托此类数据，我们揭示了覆盖3542235名个体的大规模场景、且粒度细至7.5分钟的人类移动性模型与统计特征。随后，我们分析了7.5分钟至32小时不同时间尺度下移动性模型的统计差异与偏差，发现时间尺度确实会对移动性模型产生显著影响，这表明人类移动性与时间维度存在深度耦合关系。此外，通过挖掘移动速度、停留时长、轨迹距离等多项新颖且精细化的特征，我们证实了出行方式等移动行为是人类移动性多样性的重要来源。尤为关键的是，我们指出既往研究采用的2小时采样间隔，不足以支撑对精细移动行为的深入研究。本研究不仅为时空维度下的人类移动性提供了宏观与微观的双重研究视角，还引入了此前无法获取的特征集，二者均对以人类移动性为驱动的各类相关现象研究具有重要的学术价值。