Influences of Temporal Factors on GPS-based Human Mobility Lifestyle
This work addresses urban planning and location-based services, but it is incremental as it applies existing methods to new data with limited scope.
The paper tackled the problem of identifying temporal factors affecting human mobility lifestyle from GPS data, finding that people maintain mobility habits on Thursdays and days in the second week of a month but lose habits on Fridays.
Analysis of human mobility from GPS trajectories becomes crucial in many aspects such as policy planning for urban citizens, location-based service recommendation/prediction, and especially mitigating the spread of biological and mobile viruses. In this paper, we propose a method to find temporal factors affecting the human mobility lifestyle. We collected GPS data from 100 smartphone users in Japan. We designed a model that consists of 13 temporal patterns. We then applied a multiple linear regression and found that people tend to keep their mobility habits on Thursday and the days in the second week of a month but tend to lose their habits on Friday. We also explained some reasons behind these findings.