Publication Type
Journal Article
Version
publishedVersion
Publication Date
11-2017
Abstract
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.
Keywords
Algorithms, Cell Phone, Data Collection, Geographic Information Systems, Spatio-Temporal Analysis, Time Factors
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
PLoS One
Volume
13
Issue
11
First Page
1
Last Page
15
ISSN
1932-6203
Identifier
10.1371/journal.pone.0207697
Publisher
Public Library of Science
Embargo Period
12-18-2019
Citation
LIU, Tongtong; YANG, Zheng; ZHAO, Yi; WU, Chenshu; ZHOU, Zimu; and LIU, Yunhao.
Temporal understanding of human mobility: A multi-time scale analysis. (2017). PLoS One. 13, (11), 1-15.
Available at: https://ink.library.smu.edu.sg/sis_research/4529
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1371/journal.pone.0207697