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Mobile Communication Signatures of Unemployment
Name
1609.01778.pdf
Description
Submitted version
Size
5.81 MB
Format
Adobe PDF
Checksum (MD5)
3d4bf179ab4b03ec90f534b1e7b1b022
Author(s)
Almaatouq, Abdullah
Prieto-Castrillo, Francisco
Pentland, Alex
Date Issued
2016
Publisher
Springer Nature
Citation
Almaatouq, Abdullah, Prieto-Castrillo, Francisco and Pentland, Alex. 2016. "Mobile Communication Signatures of Unemployment."
Version
Original manuscript
Abstract
© Springer International Publishing AG 2016. The mapping of populations socio-economic well-being is highly constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess; thus the speed of which policies can be designed and evaluated is limited. However, recent studies have shown the value of mobile phone data as an enabling methodology for demographic modeling and measurement. In this work, we investigate whether indicators extracted from mobile phone usage can reveal information about the socio-economical status of microregions such as districts (i.e., average spatial resolution <2.7 km). For this we examine anonymized mobile phone metadata combined with beneficiaries records from unemployment benefit program. We find that aggregated activity, social, and mobility patterns strongly correlate with unemployment. Furthermore, we construct a simple model to produce accurate reconstruction of district level unemployment from their mobile communication patterns alone. Our results suggest that reliable and cost-effective economical indicators could be built based on passively collected and anonymized mobile phone data. With similar data being collected every day by telecommunication services across the world, survey-based methods of measuring community socioeconomic status could potentially be augmented or replaced by such passive sensing methods in the future.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1007/978-3-319-47880-7_25
