Ventajas metodológicas del uso del análisis de clases latentes (LCA) para investigar en comunicación. Aplicación empírica al estudio de la confianza en la ciencia
Resumen
Este artículo examina el Análisis de Clases Latentes (LCA) como herramienta metodológica para la segmentación de audiencias en estudios de comunicación. A partir de una revisión conceptual de los métodos de clasificación —supervisados y no supervisados—, se argumenta que, en algunos casos, el LCA ofrece ventajas sustantivas frente a los enfoques tradicionales, al incorporar la incertidumbre en la asignación de los casos y modelar la heterogeneidad social desde una perspectiva probabilística. Se presenta una aplicación empírica utilizando el paquete poLCA en R y datos de la Encuesta de Percepción Social de la Ciencia y la Tecnología en España (FECYT, 2024), con el objetivo de identificar diferentes perfiles de confianza en los científicos. Los resultados ilustran cómo esta técnica permite capturar estructuras latentes que explican las variaciones en las actitudes ciudadanas hacia la ciencia. En general, el trabajo destaca la relevancia del LCA como puente entre teoría y medición en la investigación en comunicación.
Citas
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