Publication Date:
2015-11-28
Description:
Accurate and timely estimates of population characteristics are a critical input to social and economic research and policy. In industrialized economies, novel sources of data are enabling new approaches to demographic profiling, but in developing countries, fewer sources of big data exist. We show that an individual's past history of mobile phone use can be used to infer his or her socioeconomic status. Furthermore, we demonstrate that the predicted attributes of millions of individuals can, in turn, accurately reconstruct the distribution of wealth of an entire nation or to infer the asset distribution of microregions composed of just a few households. In resource-constrained environments where censuses and household surveys are rare, this approach creates an option for gathering localized and timely information at a fraction of the cost of traditional methods.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Blumenstock, Joshua -- Cadamuro, Gabriel -- On, Robert -- New York, N.Y. -- Science. 2015 Nov 27;350(6264):1073-6. doi: 10.1126/science.aac4420.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Information School, University of Washington, Seattle, WA 98195, USA. joshblum@uw.edu. ; Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA. ; School of Information, University of California, Berkeley, Berkeley, CA 94720, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26612950" target="_blank"〉PubMed〈/a〉
Keywords:
Cell Phones/*utilization
;
Censuses
;
Developing Countries/*statistics & numerical data
;
Family Characteristics
;
Humans
;
Poverty/*statistics & numerical data
;
Rwanda
;
*Social Class
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
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