Sequences of purchases in credit card data reveal lifestyles in urban populations
- Submitting institution
-
University of Exeter
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6400
- Type
- D - Journal article
- DOI
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10.1038/s41467-018-05690-8
- Title of journal
- Nature Communications
- Article number
- ARTN 3330
- First page
- -
- Volume
- 9
- Issue
- 1
- ISSN
- 2041-1723
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper was founded by Gates Foundation and UN and the Royal Society. I developed new methodologies to couple the information in credit card and mobile phone data to reveal patterns in socioeconomics. This framework helped to study protection measures for financially vulnerable users and our work has already proven its potential in a recent data2x report on gender gaps, showing how big data analysis can provide insights into women's social economic status in developing countries. https://data2x.org/wp-content/uploads/2019/05/Big-Data-and-the-Well-Being-of-Women-and-Girls_.pdf. Moreover we received a great deal of attention from the press and we published a dissemination article in The Conversation https://theconversation.com/urbanites-can-be-divided-into-six-different-tribes-to-help-make-cities-fit-for-all-102366.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -