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Assessing the quality of home detection from mobile phone data for official statistics

Vanhoof, M; Reis, F; Ploetz, T; Smoreda, Z; (2018) Assessing the quality of home detection from mobile phone data for official statistics. Journal of Official Statistics , 34 (4) pp. 935-960. 10.2478/jos-2018-0046. Green open access

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Abstract

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this paper, we focus on arguably the most important problem hindering the application of mobile phone data in official statistics: detecting home locations. We argue that current efforts to detect home locations suffer from a blind deployment of criteria to define a place of residence and from limited validation possibilities. We support our argument by analysing the performance of five home detection algorithms (HDAs) that have been applied to a large, French, Call Detailed Record (CDR) dataset (~18 million users, 5 months). Our results show that criteria choice in HDAs influences the detection of home locations for up to about 40% of users, that HDAs perform poorly when compared with a validation dataset (the 35{\deg}-gap), and that their performance is sensitive to the time period and the duration of observation. Based on our findings and experiences, we offer several recommendations for official statistics. If adopted, our recommendations would help in ensuring a more reliable use of mobile phone data vis-\`a-vis official statistics.

Type: Article
Title: Assessing the quality of home detection from mobile phone data for official statistics
Open access status: An open access version is available from UCL Discovery
DOI: 10.2478/jos-2018-0046
Publisher version: http://dx.doi.org/10.2478/jos-2018-0046
Language: English
Additional information: Copyright © Statistics Sweden. This article is published under Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)license.
Keywords: Mobile phone data; home location; home detection algorithms; official statistics; big data
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: http://discovery.ucl.ac.uk/id/eprint/10067262
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