Marketing and social networks: a criterion for detecting opinion leaders

Autores
Litterio, Arnaldo Mario; Nantes, Esteban Alberto; Larrosa, Juan Manuel Ceferino
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Purpose: The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics. Design/methodology/approach: A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model. Findings: The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods. Originality/value: This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.
Fil: Litterio, Arnaldo Mario. Universidad Nacional del Sur; Argentina
Fil: Nantes, Esteban Alberto. Universidad Nacional del Sur; Argentina
Fil: Larrosa, Juan Manuel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
Materia
INFLUENCERS
MARKETING
SOCIAL NETWORK ANALYSIS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/64664
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Marketing and social networks: a criterion for detecting opinion leadersLitterio, Arnaldo MarioNantes, Esteban AlbertoLarrosa, Juan Manuel CeferinoINFLUENCERSMARKETINGSOCIAL NETWORK ANALYSIShttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5Purpose: The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics. Design/methodology/approach: A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model. Findings: The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods. Originality/value: This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.Fil: Litterio, Arnaldo Mario. Universidad Nacional del Sur; ArgentinaFil: Nantes, Esteban Alberto. Universidad Nacional del Sur; ArgentinaFil: Larrosa, Juan Manuel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; ArgentinaEmerald2017-11-16info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/64664Litterio, Arnaldo Mario; Nantes, Esteban Alberto; Larrosa, Juan Manuel Ceferino; Marketing and social networks: a criterion for detecting opinion leaders; Emerald; European Journal of Management and Business Economics; 26; 3; 16-11-2017; 347-3662444-8451CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.emeraldinsight.com/doi/pdfplus/10.1108/EJMBE-10-2017-020info:eu-repo/semantics/altIdentifier/doi/10.1108/EJMBE-10-2017-020info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:02:44Zoai:ri.conicet.gov.ar:11336/64664instacron: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 10:02:44.64CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Marketing and social networks: a criterion for detecting opinion leaders
title Marketing and social networks: a criterion for detecting opinion leaders
spellingShingle Marketing and social networks: a criterion for detecting opinion leaders
Litterio, Arnaldo Mario
INFLUENCERS
MARKETING
SOCIAL NETWORK ANALYSIS
title_short Marketing and social networks: a criterion for detecting opinion leaders
title_full Marketing and social networks: a criterion for detecting opinion leaders
title_fullStr Marketing and social networks: a criterion for detecting opinion leaders
title_full_unstemmed Marketing and social networks: a criterion for detecting opinion leaders
title_sort Marketing and social networks: a criterion for detecting opinion leaders
dc.creator.none.fl_str_mv Litterio, Arnaldo Mario
Nantes, Esteban Alberto
Larrosa, Juan Manuel Ceferino
author Litterio, Arnaldo Mario
author_facet Litterio, Arnaldo Mario
Nantes, Esteban Alberto
Larrosa, Juan Manuel Ceferino
author_role author
author2 Nantes, Esteban Alberto
Larrosa, Juan Manuel Ceferino
author2_role author
author
dc.subject.none.fl_str_mv INFLUENCERS
MARKETING
SOCIAL NETWORK ANALYSIS
topic INFLUENCERS
MARKETING
SOCIAL NETWORK ANALYSIS
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv Purpose: The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics. Design/methodology/approach: A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model. Findings: The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods. Originality/value: This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.
Fil: Litterio, Arnaldo Mario. Universidad Nacional del Sur; Argentina
Fil: Nantes, Esteban Alberto. Universidad Nacional del Sur; Argentina
Fil: Larrosa, Juan Manuel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina
description Purpose: The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics. Design/methodology/approach: A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model. Findings: The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods. Originality/value: This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.
publishDate 2017
dc.date.none.fl_str_mv 2017-11-16
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/11336/64664
Litterio, Arnaldo Mario; Nantes, Esteban Alberto; Larrosa, Juan Manuel Ceferino; Marketing and social networks: a criterion for detecting opinion leaders; Emerald; European Journal of Management and Business Economics; 26; 3; 16-11-2017; 347-366
2444-8451
CONICET Digital
CONICET
url http://hdl.handle.net/11336/64664
identifier_str_mv Litterio, Arnaldo Mario; Nantes, Esteban Alberto; Larrosa, Juan Manuel Ceferino; Marketing and social networks: a criterion for detecting opinion leaders; Emerald; European Journal of Management and Business Economics; 26; 3; 16-11-2017; 347-366
2444-8451
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.emeraldinsight.com/doi/pdfplus/10.1108/EJMBE-10-2017-020
info:eu-repo/semantics/altIdentifier/doi/10.1108/EJMBE-10-2017-020
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
dc.publisher.none.fl_str_mv Emerald
publisher.none.fl_str_mv Emerald
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv 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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score 13.13397

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