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dc.contributor.authorLitterio, Mario
dc.contributor.authorNantes, Esteban Alberto
dc.contributor.authorLarrosa, Juan Manuel
dc.contributor.authorGómez, Liliana Julia
dc.date.accessioned2022-05-23T19:29:54Z
dc.date.available2022-05-23T19:29:54Z
dc.date.issued2017
dc.identifier.urihttps://repositoriodigital.uns.edu.ar/handle/123456789/6059
dc.description.abstractPurpose – 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.es_AR
dc.formatapplication/pdfes_AR
dc.format.extent20 págs.es_AR
dc.language.isoenges_AR
dc.publisherEmerald Publishing Limitedes_AR
dc.rightsAtribución (BY): Permite a otros distribuir, adaptar, refundir y crear a partir de la obra, incluso con fines comerciales, siempre y cuando den crédito al autor por la creación original.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSocial network analysises_AR
dc.subjectMarketinges_AR
dc.subjectInfluencerses_AR
dc.titleMarketing and social networks : a criterion for detecting opinion leaderses_AR
dcterms.accessRightsinfo:eu-repo/semantics/openAccesses_AR
dcterms.isPartOfEuropean Journal of Management and Business Economics. Emerald Publishing Limited. ISSN 2444-8451es_AR
uns.author.affiliationFil: Litterio, Mario. Universidad Nacional del Sur. Departamento de Ciencias de la Administración; Argentina.es_AR
uns.author.affiliationFil: Nantes, Esteban Alberto. Universidad Nacional del Sur. Departamento de Ciencias de la Administración; Argentina.es_AR
uns.author.affiliationFil: Larrosa, Juan Manuel. Universidad Nacional del Sur. Departamento de Economía; Argentina.es_AR
uns.author.affiliationFil: Gómez, Liliana Julia. Universidad Nacional del Sur. Departamento de Ciencias de la Administración; Argentina.es_AR
uns.type.OpenAirearticlees_AR
uns.type.SNRDartículoes_AR
uns.type.publicationVersioninfo:eu-repo/semantics/publishedVersiones_AR
uns.bibliographicCitationLitterio, M. A., Nantes, E. A., Larrosa, J. M., Gómez, L. J. (2017). Marketing and social networks: a criterion for detecting opinion leaders. European Journal of Management and Business Economics, v. 26, no. 3, pp. 347-366. Disponible en: https://repositoriodigital.uns.edu.ar/handle/123456789/6059es_AR
uns.identifier.issn2444-8451
dc.identifier.doi10.1108/EJMBE-10-2017-020


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