Marketing and social networks : a criterion for detecting opinion leaders
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...
Guardado en:
| Autores principales: | , , , |
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| Lenguaje: | Inglés |
| Publicado: |
Emerald Publishing Limited
2022
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| Materias: | |
| Acceso en línea: | https://repositoriodigital.uns.edu.ar/xmlui/handle/123456789/6059 |
| Aporte de: |
| Sumario: | 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. |
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