Belief Dynamics in Complex Social Networks
- Autores
- Gallo, Fabio R.; Abad Santos, Natalia; Simari, Gerardo I.; Martínez, María Vanina; Falappa, Marcelo Alejandro
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- People are becoming increasingly more connected to each other in social media networks. These networks are complex because in general there can be many di fferent types of relations, as well as di fferent degrees of strength for each one; moreover, these relations are dynamic because they can change over time. In this context, users' knowledge flows over the network, and modeling how this occurs - or can possibly occur - is therefore of great interest from a knowledge representation and reasoning perspective. In this paper, we focus on the problem of how a single user's knowledge base changes when exposed to a stream of news items coming from other members in the network. As a first step towards solving this problem, we identify possible solutions leveraging preexisting belief merging operators, and conclude that there is a gap that needs to be bridged between the application of such operators and a principled solution to the proposed problem.
Sociedad Argentina de Informática e Investigación Operativa (SADIO) - Materia
-
Ciencias Informáticas
social web
complex networks
belief merging operators - 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:10915/56887
Ver los metadatos del registro completo
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Belief Dynamics in Complex Social NetworksGallo, Fabio R.Abad Santos, NataliaSimari, Gerardo I.Martínez, María VaninaFalappa, Marcelo AlejandroCiencias Informáticassocial webcomplex networksbelief merging operatorsPeople are becoming increasingly more connected to each other in social media networks. These networks are complex because in general there can be many di fferent types of relations, as well as di fferent degrees of strength for each one; moreover, these relations are dynamic because they can change over time. In this context, users' knowledge flows over the network, and modeling how this occurs - or can possibly occur - is therefore of great interest from a knowledge representation and reasoning perspective. In this paper, we focus on the problem of how a single user's knowledge base changes when exposed to a stream of news items coming from other members in the network. As a first step towards solving this problem, we identify possible solutions leveraging preexisting belief merging operators, and conclude that there is a gap that needs to be bridged between the application of such operators and a principled solution to the proposed problem.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/pdf70-77http://sedici.unlp.edu.ar/handle/10915/56887enginfo:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/ASAI-04_0.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7585info: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:UNLP2025-09-29T11:06:12Zoai:sedici.unlp.edu.ar:10915/56887Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:06:12.372SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Belief Dynamics in Complex Social Networks |
title |
Belief Dynamics in Complex Social Networks |
spellingShingle |
Belief Dynamics in Complex Social Networks Gallo, Fabio R. Ciencias Informáticas social web complex networks belief merging operators |
title_short |
Belief Dynamics in Complex Social Networks |
title_full |
Belief Dynamics in Complex Social Networks |
title_fullStr |
Belief Dynamics in Complex Social Networks |
title_full_unstemmed |
Belief Dynamics in Complex Social Networks |
title_sort |
Belief Dynamics in Complex Social Networks |
dc.creator.none.fl_str_mv |
Gallo, Fabio R. Abad Santos, Natalia Simari, Gerardo I. Martínez, María Vanina Falappa, Marcelo Alejandro |
author |
Gallo, Fabio R. |
author_facet |
Gallo, Fabio R. Abad Santos, Natalia Simari, Gerardo I. Martínez, María Vanina Falappa, Marcelo Alejandro |
author_role |
author |
author2 |
Abad Santos, Natalia Simari, Gerardo I. Martínez, María Vanina Falappa, Marcelo Alejandro |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas social web complex networks belief merging operators |
topic |
Ciencias Informáticas social web complex networks belief merging operators |
dc.description.none.fl_txt_mv |
People are becoming increasingly more connected to each other in social media networks. These networks are complex because in general there can be many di fferent types of relations, as well as di fferent degrees of strength for each one; moreover, these relations are dynamic because they can change over time. In this context, users' knowledge flows over the network, and modeling how this occurs - or can possibly occur - is therefore of great interest from a knowledge representation and reasoning perspective. In this paper, we focus on the problem of how a single user's knowledge base changes when exposed to a stream of news items coming from other members in the network. As a first step towards solving this problem, we identify possible solutions leveraging preexisting belief merging operators, and conclude that there is a gap that needs to be bridged between the application of such operators and a principled solution to the proposed problem. Sociedad Argentina de Informática e Investigación Operativa (SADIO) |
description |
People are becoming increasingly more connected to each other in social media networks. These networks are complex because in general there can be many di fferent types of relations, as well as di fferent degrees of strength for each one; moreover, these relations are dynamic because they can change over time. In this context, users' knowledge flows over the network, and modeling how this occurs - or can possibly occur - is therefore of great interest from a knowledge representation and reasoning perspective. In this paper, we focus on the problem of how a single user's knowledge base changes when exposed to a stream of news items coming from other members in the network. As a first step towards solving this problem, we identify possible solutions leveraging preexisting belief merging operators, and conclude that there is a gap that needs to be bridged between the application of such operators and a principled solution to the proposed problem. |
publishDate |
2016 |
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2016-09 |
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eng |
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