Abstract
Predicting how humans move within space and time is a central topic in many scientific domains such as epidemic propagation, urban planning, and ride-sharing. However, current studies neglect individuals' preferences to explore and discover new areas. Yet, neglecting novelty-seeking activities at first glance appears to be inconsequential on the ability to understand and predict individuals' trajectories. We claim and show the opposite in this work: exploration-like visits strongly impact mobility understanding and anticipation. We start by proposing a new approach to identifying exploration visits. Based on that, we construct individuals' mobility profiles using their exploration inclinations - Scouters (i.e., extreme explorers), Routiners (i.e., extreme returners), and Regulars (i.e., with no extreme behavior). Finally, we evaluate the impacts of novelty-seeking, quality of the data, and the prediction task formulation on the theoretical and practical predictability extents. The results show the validity of our profiling and highlight the obstructive impacts of novelty-seeking activities on the predictability of human trajectories. In particular, in the next-place prediction task, from 40% to 90% of predicted locations are wrong, notably with Scouters.
Original language | English |
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Pages (from-to) | 635-649 |
Number of pages | 15 |
Journal | IEEE Transactions on Emerging Topics in Computing |
Volume | 11 |
Issue number | 3 |
DOIs | |
State | Published - Jul 1 2023 |
Externally published | Yes |
Funding
This work was supported in part by CAPES, CNPq, FAPEMIG, and FAPESP under Grant 18/23064-8 and in part by INRIA, Sorbonne UPMC, LINCS, STIC AmSud LINT under Grant 22-STIC-07.
Funders | Funder number |
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Sorbonne UPMC | 22-STIC-07 |
Institut national de recherche en informatique et en automatique (INRIA) | |
Fundação de Amparo à Pesquisa do Estado de São Paulo | 18/23064-8 |
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior | |
Conselho Nacional de Desenvolvimento Científico e Tecnológico | |
Fundação de Amparo à Pesquisa do Estado de Minas Gerais |
Keywords
- Individual mobility analytic
- mobility understanding and profiling
- predictability
- prediction