Predictability in Human Mobility based on Geographical-boundary-free and Long-time Social Media Data
Paper in proceedings, 2018

Understanding of predictability in human mobility benefits a broad spectrum such as urban planning and traffic forecasting. In human mobility studies, geotagged social media data are being gradually accepted as a user-contributed data source. It remains unclear to what extent we can use geotagged social media data to predict individual mobility. In the present study, a dataset is collected and applied which includes 652,945 geotagged tweets generated by 2,933 Swedish users covering time spans of more than one year (3.6 years on average). Based on such a dataset, human mobility predictability has been explored from three aspects: 1) time history of mobility range indicating how people diffuse in space, 2) entropy and the corresponding predictability of mobility, and 3) the limits of predictability dependent on geographical boundaries and mobility range. This study reveals a dataset that captures Twitter users' mobility where they routinely visit a couple of regions at most of the time and occasionally explore new regions. A 70% potential predictability is obtained by measuring the entropy of each individual's geotagged activity trajectory using a half-day time interval. The predictability's dependence on mobility range is prolonged when the observation of mobility is geographical-boundary-free which also decreases predictability.

entropy

Human mobility

predictability

geotagged activity trajectory

information theory

Author

Yuan Liao

Chalmers, Space, Earth and Environment, Physical Resource Theory, Physical Resource Theory 2

Sonia Yeh

Chalmers, Space, Earth and Environment, Physical Resource Theory

2018 21st International Conference on Intelligent Transportation Systems (ITSC)

2153-0017 (eISSN)

2068-2073 8569770

21st International Conference on Intelligent Transportation Systems (ITSC)
Maui, HI, USA,

Sustainable cities: the use of large amounts of data to understand and handle movement patterns and congestion

Formas, 2017-01-01 -- 2019-12-31.

Areas of Advance

Transport

Energy

Subject Categories

Transport Systems and Logistics

Human Geography

Environmental Sciences

DOI

10.1109/ITSC.2018.8569770

More information

Latest update

3/28/2019