Inference of Socioeconomic Status in a Communication Graph
- Autores
- Fixman, Martín; Berenstein, Ariel; Brea, Jorge; Minnoni, Martín; Sarraute, Carlos
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- 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.
Sociedad Argentina de Informática e Investigación Operativa (SADIO) - Materia
-
Ciencias Informáticas
mobile phone network
socio-economic correlations - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-sa/3.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/56824
Ver los metadatos del registro completo
id |
SEDICI_cfce7e38e8b6ce4c6882c07e4b3c2eb1 |
---|---|
oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/56824 |
network_acronym_str |
SEDICI |
repository_id_str |
1329 |
network_name_str |
SEDICI (UNLP) |
spelling |
Inference of Socioeconomic Status in a Communication GraphFixman, MartínBerenstein, ArielBrea, JorgeMinnoni, MartínSarraute, CarlosCiencias Informáticasmobile phone networksocio-economic correlationsIn 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.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2016-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf95-106http://sedici.unlp.edu.ar/handle/10915/56824enginfo:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/AGRANDA-09.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7569info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:38:50Zoai:sedici.unlp.edu.ar:10915/56824Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:38:50.579SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Inference of Socioeconomic Status in a Communication Graph |
title |
Inference of Socioeconomic Status in a Communication Graph |
spellingShingle |
Inference of Socioeconomic Status in a Communication Graph Fixman, Martín Ciencias Informáticas mobile phone network socio-economic correlations |
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 |
dc.creator.none.fl_str_mv |
Fixman, Martín Berenstein, Ariel Brea, Jorge Minnoni, Martín Sarraute, Carlos |
author |
Fixman, Martín |
author_facet |
Fixman, Martín Berenstein, Ariel Brea, Jorge Minnoni, Martín Sarraute, Carlos |
author_role |
author |
author2 |
Berenstein, Ariel Brea, Jorge Minnoni, Martín Sarraute, Carlos |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas mobile phone network socio-economic correlations |
topic |
Ciencias Informáticas mobile phone network socio-economic correlations |
dc.description.none.fl_txt_mv |
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. Sociedad Argentina de Informática e Investigación Operativa (SADIO) |
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. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/56824 |
url |
http://sedici.unlp.edu.ar/handle/10915/56824 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/AGRANDA-09.pdf info:eu-repo/semantics/altIdentifier/issn/2451-7569 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-sa/3.0/ Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-sa/3.0/ Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) |
dc.format.none.fl_str_mv |
application/pdf 95-106 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
SEDICI (UNLP) |
collection |
SEDICI (UNLP) |
instname_str |
Universidad Nacional de La Plata |
instacron_str |
UNLP |
institution |
UNLP |
repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
_version_ |
1842260248202575872 |
score |
13.13397 |