Social network analysis for automatic ranking of political stakeholders: A case study
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| Autores: | , , , |
|---|---|
| Formato: | comunicación de congreso |
| Fecha de Publicación: | 2022 |
| Descripción: | This article exposes the way in which the creation of a new method for calculating the popularity of stake holders in social networks can support political data analysis experts. The definition of a new formula for estimating popularity allowed us to have a new method that, together with other previously existing ones, allows us to build a multidimensional interpretation of reality. The construction of a method that would seem like a computational scientific curiosity has significant impacts for experts who carry out political analysis. The new ranking algorithm called BOPRank made it possible to identify political actors in a different way than known algorithms. While a wellknown algorithm showed popularity as a result of the work of campaign teams on social networks, the new algorithm reflected popularity obtained as a result of the reaction of the public on social networks. |
| País: | Kérwá |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Kérwá |
| Lenguaje: | Español |
| OAI Identifier: | oai:kerwa.ucr.ac.cr:10669/90286 |
| Acceso en línea: | https://ieeexplore.ieee.org/document/9959920 https://hdl.handle.net/10669/90286 |
| Palabra clave: | ANÁLISIS DE DATOS MEDIOS SOCIALES CLASIFICACIÓN ESTUDIO DE CASO POLÍTICA |