Minería de comentarios en la red social X sobre la percepción de la seguridad en la ciudadanía ecuatoriana
Mining comments from the social network x on the security perceptions of Ecuadorian citizens
DOI:
https://doi.org/10.53591/iti.v17i24.2609Palabras clave:
seguridad ciudadana, minería de texto, redes sociales, sentimiento, LDA, EcuadorResumen
Contexto: En el actual contexto de creciente atención hacia la seguridad ciudadana en Ecuador, las redes sociales se han consolidado como espacios donde se manifiestan percepciones colectivas sobre la violencia y el crimen. Objetivo: Este estudio tiene como propósito analizar publicaciones extraídas de la red social X (antes Twitter), con el fin de identificar patrones discursivos vinculados a la inseguridad, mediante técnicas computacionales aplicadas a datos textuales. Técnica: La muestra estuvo compuesta por más de 2.000 publicaciones geolocalizadas en seis cantones: Guayaquil, Quito, Cuenca, Portoviejo, Manta y Durán, recolectadas en seis cortes entre junio y julio de 2025. El preprocesamiento incluyó la depuración de duplicados, normalización léxica y análisis de tokens. Se emplearon técnicas de minería de texto como el análisis de frecuencia de términos, generación de bigramas, clasificación léxica de sentimiento y modelado temático. Resultados: El análisis reflejó una alta recurrencia de términos vinculados a hechos delictivos y una predominancia de mensajes con polaridad negativa, particularmente en Guayaquil, Manta y Durán. A través del modelo de clasificación Latent Dirichlet Allocation (LDA) se identificaron cinco tópicos recurrentes que agrupan diferentes expresiones discursivas sobre la inseguridad. Además, se sugiere el empleo de otros modelos de clasificación como Naive Bayes para estimar la polaridad de nuevas publicaciones, mediante una mayor proporción de datos previamente etiquetados. Conclusión: Este estudio destaca la importancia del procesamiento de lenguaje natural en combinación con técnicas de clasificación para facilitar el reconocimiento de patrones de interés dentro de la seguridad ciudadana del país, desde la percepción de usuarios de redes sociales.
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