#6178. On estimating the predictability of human mobility: the role of routine

September 2026publication date
Proposal available till 13-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Computational Mathematics;
Modeling and Simulation;
Computer Science Applications;
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More details about the manuscript: Science Citation Index Expanded or/and Social Sciences Citation Index
Abstract:
Given the difficulties in predicting human behavior, one may wish to establish bounds on our ability to accurately perform such predictions. In the case of mobility-related behavior, there exists a fundamental technique to estimate the predictability of an individual’s mobility, as expressed in a given dataset. Although useful in several scenarios, this technique focused on human mobility as a monolithic entity, which poses challenges to understanding different types of behavior that may be hard to predict. In this paper, we propose to study predictability in terms of two components of human mobility: routine and novelty, where routine is related to preferential returns, and novelty is related to exploration. Viewing one’s mobility in terms of these two components allows us to identify important patterns about the predictability of one’s mobility. Additionally, we argue that mobility behavior in the novelty component is hard to predict if we rely on the history of visited locations (as the predictability technique does), and therefore we here focus on analyzing what affects the predictability of one’s routine. To that end, we propose a technique that allows us to (i) quantify the effect of novelty on predictability, and (ii) gauge how much one’s routine deviates from a reference routine that is completely predictable, therefore estimating the amount of hard-to-predict behavior in one’s routine. Finally, we rely on previously proposed metrics, as well as a newly proposed one, to understand what affects the predictability of a person’s routine.
Keywords:
Entropy; Human mobility; Mobility metrics; Predictability

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