Clusterización electoral de los municipios de Antioquia mediante algoritmo de clasificación no supervisada K-Means
DOI:
https://doi.org/10.33571/rpolitec.v21n42a6Palabras clave:
Electoral, Democracia, Política, Agrupamiento, EstadísticaResumen
Este estudio tiene como objetivo aplicar el algoritmo de clasificación no supervisada K-Means para identificar patrones de votación de los municipios del departamento de Antioquia según su comportamiento electoral en las elecciones al Senado de 2022. Para esto se seleccionaron los partidos políticos con una participación superior al 5 % del total de votos en el departamento. Los resultados permitieron identificar cuatro clústeres con patrones electorales claros: una tendencia liberal predominante, un grupo equilibrado entre partidos, una agrupación de orientación hacia el Centro Democrático y un grupo de predominio conservador. La metodología demostró ser eficaz para detectar patrones electorales territoriales, evidenciando la utilidad del aprendizaje automático en el análisis electoral y su potencial aplicación en estudios políticos.
This study aims to classify the municipalities of the department of Antioquia according to their electoral behavior in the 2022 Senate elections, through the application of the unsupervised classification algorithm K-Means. Political parties with a participation greater than 5% of the total votes in the department were selected. The results allowed the identification of four clústers with clear electoral patterns: one with a predominant liberal tendency, another showing a balanced distribution among parties, a group oriented toward the Centro Democrático party, and a group with a conservative predominance. The methodology proved effective in detecting territorial electoral patterns, demonstrating the usefulness of machine learning techniques in electoral analysis and their potential application in comparative political studies.
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Derechos de autor 2025 José Sebastian Díaz-Arguello

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