Social Influence in Group Recommender Systems
- Autores
- Schiaffino, Silvia Noemi; Christensen, Ingrid Alina
- Año de publicación
- 2014
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Purpose – The purpose of this paper is to propose an approach to generate recommendations for groups on the basis of social factors extracted from a social network. Group recommendation techniques traditionally assumed users were independent individuals, ignoring the effects of social interaction and relationships among users. In this work the authors analyse the social factors available in social networks in the light of sociological theories which endorse individuals’ susceptibility to influence within a group. Design/methodology/approach – The approach proposed is based on the creation of a group model in two stages: identifying the items that are representative of the majority's preferences, and analysing members’ similarity; and extracting potential influence from members’ interactions in a social network to predict a group's opinion on each item. Findings – The promising results obtained when evaluating the approach in the movie domain suggest that individual opinions tend to be accommodated to group satisfaction, as demonstrated by the incidence of the aforementioned factors in collective behaviour, as endorsed by sociological research. Moreover the findings suggest that these factors have dissimilar impacts on group satisfaction. Originality/value – The results obtained provide clues about how social influence exerted within groups could alter individuals’ opinions when a group has a common goal. There is limited research in this area exploring social influence in group recommendations; thus the originality of this perspective lies in the use of sociological theory to explain social influence in groups of users, and the flexibility of the approach to be applied in any domain. The findings could be helpful for group recommender systems developers both at research and commercial levels.
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Christensen, Ingrid Alina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina - Materia
-
Social Influence
Group Recommendation
Social Recommendation
Online Social Networks - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/6794
Ver los metadatos del registro completo
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Social Influence in Group Recommender SystemsSchiaffino, Silvia NoemiChristensen, Ingrid AlinaSocial InfluenceGroup RecommendationSocial RecommendationOnline Social Networkshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Purpose – The purpose of this paper is to propose an approach to generate recommendations for groups on the basis of social factors extracted from a social network. Group recommendation techniques traditionally assumed users were independent individuals, ignoring the effects of social interaction and relationships among users. In this work the authors analyse the social factors available in social networks in the light of sociological theories which endorse individuals’ susceptibility to influence within a group. Design/methodology/approach – The approach proposed is based on the creation of a group model in two stages: identifying the items that are representative of the majority's preferences, and analysing members’ similarity; and extracting potential influence from members’ interactions in a social network to predict a group's opinion on each item. Findings – The promising results obtained when evaluating the approach in the movie domain suggest that individual opinions tend to be accommodated to group satisfaction, as demonstrated by the incidence of the aforementioned factors in collective behaviour, as endorsed by sociological research. Moreover the findings suggest that these factors have dissimilar impacts on group satisfaction. Originality/value – The results obtained provide clues about how social influence exerted within groups could alter individuals’ opinions when a group has a common goal. There is limited research in this area exploring social influence in group recommendations; thus the originality of this perspective lies in the use of sociological theory to explain social influence in groups of users, and the flexibility of the approach to be applied in any domain. The findings could be helpful for group recommender systems developers both at research and commercial levels.Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Christensen, Ingrid Alina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaEmerald Group Publishing Limited2014-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/6794Schiaffino, Silvia Noemi; Christensen, Ingrid Alina; Social Influence in Group Recommender Systems; Emerald Group Publishing Limited; Online Information Review; 38; 4; 11-2014; 524-5421468-4527enginfo:eu-repo/semantics/altIdentifier/url/http://www.emeraldinsight.com/doi/abs/10.1108/OIR-08-2013-0187?journalCode=oirinfo:eu-repo/semantics/altIdentifier/doi/10.1108/OIR-08-2013-0187info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:47Zoai:ri.conicet.gov.ar:11336/6794instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:47.413CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Social Influence in Group Recommender Systems |
title |
Social Influence in Group Recommender Systems |
spellingShingle |
Social Influence in Group Recommender Systems Schiaffino, Silvia Noemi Social Influence Group Recommendation Social Recommendation Online Social Networks |
title_short |
Social Influence in Group Recommender Systems |
title_full |
Social Influence in Group Recommender Systems |
title_fullStr |
Social Influence in Group Recommender Systems |
title_full_unstemmed |
Social Influence in Group Recommender Systems |
title_sort |
Social Influence in Group Recommender Systems |
dc.creator.none.fl_str_mv |
Schiaffino, Silvia Noemi Christensen, Ingrid Alina |
author |
Schiaffino, Silvia Noemi |
author_facet |
Schiaffino, Silvia Noemi Christensen, Ingrid Alina |
author_role |
author |
author2 |
Christensen, Ingrid Alina |
author2_role |
author |
dc.subject.none.fl_str_mv |
Social Influence Group Recommendation Social Recommendation Online Social Networks |
topic |
Social Influence Group Recommendation Social Recommendation Online Social Networks |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Purpose – The purpose of this paper is to propose an approach to generate recommendations for groups on the basis of social factors extracted from a social network. Group recommendation techniques traditionally assumed users were independent individuals, ignoring the effects of social interaction and relationships among users. In this work the authors analyse the social factors available in social networks in the light of sociological theories which endorse individuals’ susceptibility to influence within a group. Design/methodology/approach – The approach proposed is based on the creation of a group model in two stages: identifying the items that are representative of the majority's preferences, and analysing members’ similarity; and extracting potential influence from members’ interactions in a social network to predict a group's opinion on each item. Findings – The promising results obtained when evaluating the approach in the movie domain suggest that individual opinions tend to be accommodated to group satisfaction, as demonstrated by the incidence of the aforementioned factors in collective behaviour, as endorsed by sociological research. Moreover the findings suggest that these factors have dissimilar impacts on group satisfaction. Originality/value – The results obtained provide clues about how social influence exerted within groups could alter individuals’ opinions when a group has a common goal. There is limited research in this area exploring social influence in group recommendations; thus the originality of this perspective lies in the use of sociological theory to explain social influence in groups of users, and the flexibility of the approach to be applied in any domain. The findings could be helpful for group recommender systems developers both at research and commercial levels. Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina Fil: Christensen, Ingrid Alina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina |
description |
Purpose – The purpose of this paper is to propose an approach to generate recommendations for groups on the basis of social factors extracted from a social network. Group recommendation techniques traditionally assumed users were independent individuals, ignoring the effects of social interaction and relationships among users. In this work the authors analyse the social factors available in social networks in the light of sociological theories which endorse individuals’ susceptibility to influence within a group. Design/methodology/approach – The approach proposed is based on the creation of a group model in two stages: identifying the items that are representative of the majority's preferences, and analysing members’ similarity; and extracting potential influence from members’ interactions in a social network to predict a group's opinion on each item. Findings – The promising results obtained when evaluating the approach in the movie domain suggest that individual opinions tend to be accommodated to group satisfaction, as demonstrated by the incidence of the aforementioned factors in collective behaviour, as endorsed by sociological research. Moreover the findings suggest that these factors have dissimilar impacts on group satisfaction. Originality/value – The results obtained provide clues about how social influence exerted within groups could alter individuals’ opinions when a group has a common goal. There is limited research in this area exploring social influence in group recommendations; thus the originality of this perspective lies in the use of sociological theory to explain social influence in groups of users, and the flexibility of the approach to be applied in any domain. The findings could be helpful for group recommender systems developers both at research and commercial levels. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-11 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/6794 Schiaffino, Silvia Noemi; Christensen, Ingrid Alina; Social Influence in Group Recommender Systems; Emerald Group Publishing Limited; Online Information Review; 38; 4; 11-2014; 524-542 1468-4527 |
url |
http://hdl.handle.net/11336/6794 |
identifier_str_mv |
Schiaffino, Silvia Noemi; Christensen, Ingrid Alina; Social Influence in Group Recommender Systems; Emerald Group Publishing Limited; Online Information Review; 38; 4; 11-2014; 524-542 1468-4527 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://www.emeraldinsight.com/doi/abs/10.1108/OIR-08-2013-0187?journalCode=oir info:eu-repo/semantics/altIdentifier/doi/10.1108/OIR-08-2013-0187 info:eu-repo/semantics/altIdentifier/doi/ |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Emerald Group Publishing Limited |
publisher.none.fl_str_mv |
Emerald Group Publishing Limited |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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