Abstract
Human mobility literature is limited in their ability to capture the novelty-seeking or the exploratory tendency of individuals. Mainly, the vast majority of mobility prediction models rely uniquely on the history of visited locations (as captured in the input dataset) to predict future visits. This hinders the prediction of new unseen places and reduces prediction accuracy. In this paper, we show that a two-dimensional modeling of human mobility, which explicitly captures both regular and exploratory behaviors, yields a powerful characterization of users. Using such model, we identify the existence of three distinct mobility profiles with regard to the exploration phenomenon - Scouters (i.e., extreme explorers), Routiners (i.e., extreme returners), and Regulars (i.e., without extreme behavior). Further, we extract and analyze the mobility traits specific to each profile. We then investigate temporal and spatial patterns in each mobility profile and show the presence of recurrent visiting behavior of individuals even in their novelty-seeking moments. Our results unveil important novelty preferences of people, which are ignored by literature prediction models. Finally, we show that prediction accuracy is dramatically affected by exploration moments of individuals. We then discuss how our profiling methodology could be leveraged to improve prediction.
Original language | English |
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Title of host publication | Proceedings of the 28th International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2020 |
Editors | Chang-Tien Lu, Fusheng Wang, Goce Trajcevski, Yan Huang, Shawn Newsam, Li Xiong |
Publisher | Association for Computing Machinery |
Pages | 314-324 |
Number of pages | 11 |
ISBN (Electronic) | 9781450380195 |
DOIs | |
State | Published - Nov 3 2020 |
Externally published | Yes |
Event | 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2020 - Virtual, Online, United States Duration: Nov 3 2020 → Nov 6 2020 |
Publication series
Name | GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems |
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Conference
Conference | 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2020 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 11/3/20 → 11/6/20 |
Funding
We would like to thank the research agencies CAPES, CNPq, FAPEMIG, and FAPESP (grant 18/23064-8) and the support from INRIA, Sorbonne UPMC, LINCS, ANR (French National Research Agency) MITIK project - call PRC AAPG2019.
Keywords
- Exploration
- Individual Mobility
- Mobility Profiling