2021
DOI: 10.1140/epjds/s13688-021-00304-8
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On estimating the predictability of human mobility: the role of routine

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… Show more

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Cited by 19 publications
(5 citation statements)
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“…That said, we note that the median predictions remain low across the full range of values for all covariates. This reflects the very large spread in observed displacements, even for seemingly comparable contexts, and is representative of the significant challenge of producing accurate predictions of human mobility with macrolevel models ( 60 , 61 ).…”
Section: Resultsmentioning
confidence: 77%
“…That said, we note that the median predictions remain low across the full range of values for all covariates. This reflects the very large spread in observed displacements, even for seemingly comparable contexts, and is representative of the significant challenge of producing accurate predictions of human mobility with macrolevel models ( 60 , 61 ).…”
Section: Resultsmentioning
confidence: 77%
“…Therefore, our method makes the predictability upper bound tighter. When considering the predictability of external factors, partly researchers focus primarily on the routine component with the goal of showing that there are patterns in one's hard-to-predict [9]. In order to quantify predictability, this paper creates a baseline sequence, by comparing it with the person's actual mobility trace to obtain the deviation of predictability between the original sequence and the baseline.…”
Section: Predictability Considering External Factorsmentioning
confidence: 99%
“…Here we place our emphasis on next location prediction, a vital task in human mobility modeling at individual level [14]. A body of work leverages machine learning methods to tackle this problem due to the sequential nature of mobility behavior.…”
Section: Introductionmentioning
confidence: 99%