Social Events in a Time-Varying Mobile Phone Graph
- Autores
- Sarraute, Carlos; Brea, Jorge; Burroni, Javier; Wehmuth, Klaus; Ziviani, Arthur; Alvarez Hamelin, José I.
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- The large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobile phones allows us, not only to infer social networks between individuals, but also to observe the movements of these individuals in space and time. In this work, we investigate how these two related sources of information can be integrated within the context of detecting and analyzing large social events. We show that large social events can be characterized not only by an anomalous increase in activity of the antennas in the neighborhood of the event, but also by an increase in social relationships of the attendants present in the event. Moreover, having detected a large social event via increased antenna activity, we can use the network connections to infer whether an unobserved user was present at the event. More precisely, we address the following three challenges: (i) automatically detecting large social events via increased antenna activity; (ii) characterizing the social cohesion of the detected event; and (iii) analyzing the feasibility of inferring whether unobserved users were in the event.
Sociedad Argentina de Informática e Investigación Operativa (SADIO) - Materia
-
Ciencias Informáticas
big data
event antenna
Teléfono Celular - 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:10915/51979
Ver los metadatos del registro completo
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Social Events in a Time-Varying Mobile Phone GraphSarraute, CarlosBrea, JorgeBurroni, JavierWehmuth, KlausZiviani, ArthurAlvarez Hamelin, José I.Ciencias Informáticasbig dataevent antennaTeléfono CelularThe large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobile phones allows us, not only to infer social networks between individuals, but also to observe the movements of these individuals in space and time. In this work, we investigate how these two related sources of information can be integrated within the context of detecting and analyzing large social events. We show that large social events can be characterized not only by an anomalous increase in activity of the antennas in the neighborhood of the event, but also by an increase in social relationships of the attendants present in the event. Moreover, having detected a large social event via increased antenna activity, we can use the network connections to infer whether an unobserved user was present at the event. More precisely, we address the following three challenges: (i) automatically detecting large social events via increased antenna activity; (ii) characterizing the social cohesion of the detected event; and (iii) analyzing the feasibility of inferring whether unobserved users were in the event.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2015-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf43-49http://sedici.unlp.edu.ar/handle/10915/51979enginfo:eu-repo/semantics/altIdentifier/url/http://44jaiio.sadio.org.ar/sites/default/files/agranda43-49.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:UNLP2025-09-10T12:07:47Zoai:sedici.unlp.edu.ar:10915/51979Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 12:07:48.114SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Social Events in a Time-Varying Mobile Phone Graph |
title |
Social Events in a Time-Varying Mobile Phone Graph |
spellingShingle |
Social Events in a Time-Varying Mobile Phone Graph Sarraute, Carlos Ciencias Informáticas big data event antenna Teléfono Celular |
title_short |
Social Events in a Time-Varying Mobile Phone Graph |
title_full |
Social Events in a Time-Varying Mobile Phone Graph |
title_fullStr |
Social Events in a Time-Varying Mobile Phone Graph |
title_full_unstemmed |
Social Events in a Time-Varying Mobile Phone Graph |
title_sort |
Social Events in a Time-Varying Mobile Phone Graph |
dc.creator.none.fl_str_mv |
Sarraute, Carlos Brea, Jorge Burroni, Javier Wehmuth, Klaus Ziviani, Arthur Alvarez Hamelin, José I. |
author |
Sarraute, Carlos |
author_facet |
Sarraute, Carlos Brea, Jorge Burroni, Javier Wehmuth, Klaus Ziviani, Arthur Alvarez Hamelin, José I. |
author_role |
author |
author2 |
Brea, Jorge Burroni, Javier Wehmuth, Klaus Ziviani, Arthur Alvarez Hamelin, José I. |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas big data event antenna Teléfono Celular |
topic |
Ciencias Informáticas big data event antenna Teléfono Celular |
dc.description.none.fl_txt_mv |
The large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobile phones allows us, not only to infer social networks between individuals, but also to observe the movements of these individuals in space and time. In this work, we investigate how these two related sources of information can be integrated within the context of detecting and analyzing large social events. We show that large social events can be characterized not only by an anomalous increase in activity of the antennas in the neighborhood of the event, but also by an increase in social relationships of the attendants present in the event. Moreover, having detected a large social event via increased antenna activity, we can use the network connections to infer whether an unobserved user was present at the event. More precisely, we address the following three challenges: (i) automatically detecting large social events via increased antenna activity; (ii) characterizing the social cohesion of the detected event; and (iii) analyzing the feasibility of inferring whether unobserved users were in the event. Sociedad Argentina de Informática e Investigación Operativa (SADIO) |
description |
The large-scale study of human mobility has been significantly enhanced over the last decade by the massive use of mobile phones in urban populations. Studying the activity of mobile phones allows us, not only to infer social networks between individuals, but also to observe the movements of these individuals in space and time. In this work, we investigate how these two related sources of information can be integrated within the context of detecting and analyzing large social events. We show that large social events can be characterized not only by an anomalous increase in activity of the antennas in the neighborhood of the event, but also by an increase in social relationships of the attendants present in the event. Moreover, having detected a large social event via increased antenna activity, we can use the network connections to infer whether an unobserved user was present at the event. More precisely, we address the following three challenges: (i) automatically detecting large social events via increased antenna activity; (ii) characterizing the social cohesion of the detected event; and (iii) analyzing the feasibility of inferring whether unobserved users were in the event. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-09 |
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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 |
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conferenceObject |
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dc.language.none.fl_str_mv |
eng |
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eng |
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