Characteristics of human mobility patterns revealed by high-frequency cell-phone position data
Abstract Human mobility is an important characteristic of human behavior, but since tracking personalized position to high temporal and spatial resolution is difficult, most studies on human mobility patterns rely on sparsely sampled position data. In this work, we re-examined human mobility pattern...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-01-01
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| Series: | EPJ Data Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1140/epjds/s13688-021-00261-2 |
| _version_ | 1818393405045080064 |
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| author | Chen Zhao An Zeng Chi Ho Yeung |
| author_facet | Chen Zhao An Zeng Chi Ho Yeung |
| author_sort | Chen Zhao |
| collection | DOAJ |
| description | Abstract Human mobility is an important characteristic of human behavior, but since tracking personalized position to high temporal and spatial resolution is difficult, most studies on human mobility patterns rely on sparsely sampled position data. In this work, we re-examined human mobility patterns via comprehensive cell-phone position data recorded at a high frequency up to every second. We constructed human mobility networks and found that individuals exhibit origin-dependent, path-preferential patterns in their short time-scale mobility. These behaviors are prominent when the temporal resolution of the data is high, and are thus overlooked in most previous studies. Incorporating measured quantities from our high frequency data into conventional human mobility models shows inconsistent statistical results. We finally revealed that the individual preferential transition mechanism characterized by the first-order Markov process can quantitatively reproduce the observed travel patterns at both individual and population levels at all relevant time-scales. |
| first_indexed | 2024-12-14T05:44:47Z |
| format | Article |
| id | doaj.art-46073632bc5c44ffa6e869a5370b155c |
| institution | Directory Open Access Journal |
| issn | 2193-1127 |
| language | English |
| last_indexed | 2024-12-14T05:44:47Z |
| publishDate | 2021-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EPJ Data Science |
| spelling | doaj.art-46073632bc5c44ffa6e869a5370b155c2022-12-21T23:14:54ZengSpringerOpenEPJ Data Science2193-11272021-01-0110111410.1140/epjds/s13688-021-00261-2Characteristics of human mobility patterns revealed by high-frequency cell-phone position dataChen Zhao0An Zeng1Chi Ho Yeung2College of Computer and Cyber Security, Hebei Normal UniversitySchool of Systems Science, Beijing Normal UniversityDepartment of Science and Environmental Studies, The Education University of Hong KongAbstract Human mobility is an important characteristic of human behavior, but since tracking personalized position to high temporal and spatial resolution is difficult, most studies on human mobility patterns rely on sparsely sampled position data. In this work, we re-examined human mobility patterns via comprehensive cell-phone position data recorded at a high frequency up to every second. We constructed human mobility networks and found that individuals exhibit origin-dependent, path-preferential patterns in their short time-scale mobility. These behaviors are prominent when the temporal resolution of the data is high, and are thus overlooked in most previous studies. Incorporating measured quantities from our high frequency data into conventional human mobility models shows inconsistent statistical results. We finally revealed that the individual preferential transition mechanism characterized by the first-order Markov process can quantitatively reproduce the observed travel patterns at both individual and population levels at all relevant time-scales.https://doi.org/10.1140/epjds/s13688-021-00261-2Human mobilityMobile phoneHigh frequency data |
| spellingShingle | Chen Zhao An Zeng Chi Ho Yeung Characteristics of human mobility patterns revealed by high-frequency cell-phone position data EPJ Data Science Human mobility Mobile phone High frequency data |
| title | Characteristics of human mobility patterns revealed by high-frequency cell-phone position data |
| title_full | Characteristics of human mobility patterns revealed by high-frequency cell-phone position data |
| title_fullStr | Characteristics of human mobility patterns revealed by high-frequency cell-phone position data |
| title_full_unstemmed | Characteristics of human mobility patterns revealed by high-frequency cell-phone position data |
| title_short | Characteristics of human mobility patterns revealed by high-frequency cell-phone position data |
| title_sort | characteristics of human mobility patterns revealed by high frequency cell phone position data |
| topic | Human mobility Mobile phone High frequency data |
| url | https://doi.org/10.1140/epjds/s13688-021-00261-2 |
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