Inference of Socioeconomic Status in a Communication Graph

In this work, we examine the socio-economic correlations present among users in a mobile phone network in Mexico. First, we find that the distribution of income for a subset of users –for which we have income information given by a large bank in Mexico– follows closely, but not exactly, the income d...

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Detalles Bibliográficos
Autores principales:	Fixman, Martín, Berenstein, Ariel, Brea, Jorge, Minnoni, Martín, Sarraute, Carlos
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2016
Materias:	Ciencias Informáticas mobile phone network socio-economic correlations
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/56824 http://45jaiio.sadio.org.ar/sites/default/files/AGRANDA-09.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-56824
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas mobile phone network socio-economic correlations
spellingShingle	Ciencias Informáticas mobile phone network socio-economic correlations Fixman, Martín Berenstein, Ariel Brea, Jorge Minnoni, Martín Sarraute, Carlos Inference of Socioeconomic Status in a Communication Graph
topic_facet	Ciencias Informáticas mobile phone network socio-economic correlations
description	In this work, we examine the socio-economic correlations present among users in a mobile phone network in Mexico. First, we find that the distribution of income for a subset of users –for which we have income information given by a large bank in Mexico– follows closely, but not exactly, the income distribution for the whole population of Mexico. We also show the existence of a strong socio-economic homophily in the mobile phone network, where users linked in the network are more likely to have similar income. The main contribution of this work is that we leverage this homophily in order to propose a methodology, based on Bayesian statistics, to infer the socio-economic status for a large subset of users in the network (for which we have no banking information). With our proposed algorithm, we achieve an accuracy of 0.71 in a two-class classification problem (low and high income) which significantly outperforms a simpler method based on a frequentist approach. Finally, we extend the two-class classification problem to multiple classes by using the Dirichlet distribution.
format	Objeto de conferencia Objeto de conferencia
author	Fixman, Martín Berenstein, Ariel Brea, Jorge Minnoni, Martín Sarraute, Carlos
author_facet	Fixman, Martín Berenstein, Ariel Brea, Jorge Minnoni, Martín Sarraute, Carlos
author_sort	Fixman, Martín
title	Inference of Socioeconomic Status in a Communication Graph
title_short	Inference of Socioeconomic Status in a Communication Graph
title_full	Inference of Socioeconomic Status in a Communication Graph
title_fullStr	Inference of Socioeconomic Status in a Communication Graph
title_full_unstemmed	Inference of Socioeconomic Status in a Communication Graph
title_sort	inference of socioeconomic status in a communication graph
publishDate	2016
url	http://sedici.unlp.edu.ar/handle/10915/56824 http://45jaiio.sadio.org.ar/sites/default/files/AGRANDA-09.pdf
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bdutipo_str	Repositorios
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Inference of Socioeconomic Status in a Communication Graph

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