Abstract
Recent seminal works on human mobility have shown that individuals constantly exploit a small set of repeatedly visited locations1-3. A concurrent study has emphasized the explorative nature of human behaviour, showing that the number of visited places grows steadily over time4-7. How to reconcile these seemingly contradicting facts remains an open question. Here, we analyse high-resolution multi-year traces of ~40,000 individuals from 4 datasets and show that this tension vanishes when the long-term evolution of mobility patterns is considered. We reveal that mobility patterns evolve significantly yet smoothly, and that the number of familiar locations an individual visits at any point is a conserved quantity with a typical size of ~25. We use this finding to improve state-of-the-art modelling of human mobility4,8. Furthermore, shifting the attention from aggregated quantities to individual behaviour, we show that the size of an individual's set of preferred locations correlates with their number of social interactions. This result suggests a connection between the conserved quantity we identify, which as we show cannot be understood purely on the basis of time constraints, and the 'Dunbar number'9,10 describing a cognitive upper limit to an individual's number of social relations. We anticipate that our work will spark further research linking the study of human mobility and the cognitive and behavioural sciences.
Highlights
Copyright: City Research Online aims to make research outputs of City, University of London available to a wider audience
Recent studies based on the analysis of human digital traces including mobile phone records,[14, 15] online location-based social networks,[16,17,18,19,20] and Global Positioning System (GPS) location data of vehicles[21,22,23,24,25,26] have shown that individuals universally exhibit a markedly regular pattern characterized by few locations, or points of interest,[27], where they return regularly[6], and predictably.[4]
We find that the total number of unique locations Li(t) an individual i has discovered up to time t grows as Li ∝ tαi (Fig. 1b), and that individuals’ exploration is homogeneous across the populations studied, with αi peaked around α (Lifelog: α = 0.71, Copenhagen Networks Study (CNS): α = 0.63, MDC: α = 0.68, Reality Mining dataset (RM): α = 0.76) (Fig. 1c)
Summary
RM dataset: The Reality Mining project was conducted from 2004-2005 at the MIT Media Laboratory It measured 94 subjects using mobile phones over the course of nine months. Participants’ position over time was estimated combining their smart-phones WiFi and GPS data using the method described in[68] (see Supplementary Note 1.1, and Supplementary Figure 6). Data collection for the Sony dataset has been approved by the Sony Mobile Logging Board and informed consent has been obtained for all study participants according to the Sony Mobile Application Terms of Service and the Sony Mobile Privacy Policy. Following Nokia’s privacy policy, individuals participating in the study provided informed consent.[50] The Lausanne Mobile Data Challenge experiment involves 62% male and 38% female participants, where the age range 22-33 year-old accounts for roughly 2/3 of the population.[71]
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