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Comprensión del discurso sobre salud mental en Reddit con transformadores y explicabilidad
Irene Sánchez Rodríguez1,2, John Bianchi3,4, Fabio Pinelli3
1Molecular Mind Lab, IMT School for Advanced Studies Lucca, Lucca, 55100, Italy. irene.sanchez@imtlucca.it.
Scientific reports
|January 31, 2026
Resumen
Este estudio utilizó IA para analizar discusiones sobre salud mental en Reddit, clasificando publicaciones sobre ansiedad, depresión, trastorno bipolar y trastorno límite de la personalidad (TLP). Los hallazgos revelan distintos patrones lingüísticos, lo que ayuda a comprender las comunidades de apoyo en línea.
Área de la Ciencia:
- Lingüística computacional; Informática de la salud mental; Análisis de redes sociales
Sus antecedentes:
- Las plataformas de redes sociales albergan discusiones significativas sobre salud mental.
- Comprender el discurso en línea es crucial para el apoyo y la investigación en salud mental.
- Los subreddits especializados tienen como objetivo brindar apoyo enfocado para diversas condiciones de salud mental.
Objetivo del estudio:
- Clasificar publicaciones de Reddit relacionadas con la ansiedad, la depresión, el trastorno bipolar y el trastorno límite de la personalidad (TLP).
- Evaluar la alineación de las conversaciones de los subreddits con su enfoque de salud mental previsto.
- Identificar patrones lingüísticos que caracterizan las discusiones de condiciones de salud mental específicas.
Principales métodos:
- Se emplearon modelos de transformadores preentrenados (BERT y MentalBERT) ajustados para la clasificación de texto.
- Se utilizaron explicaciones interpretables localesagnósticas del modelo (LIME) para la interpretabilidad del modelo.
- El análisis se centró en publicaciones de subreddits especializados dedicados a condiciones de salud mental.
Principales resultados:
- Los modelos de clasificación lograron una precisión promedio del 82%, y MentalBERT mostró un rendimiento ligeramente superior.
- Se identificaron patrones lingüísticos distintos para diferentes condiciones (por ejemplo, inestabilidad del estado de ánimo en el trastorno bipolar, regulación emocional en el TLP).
- El estudio demostró la efectividad de la IA en el análisis y la comprensión del discurso en línea sobre salud mental.
Conclusiones:
- Los modelos de IA pueden clasificar eficazmente los temas de salud mental en las redes sociales y evaluar la alineación de la comunidad.
- La identificación del uso específico del lenguaje proporciona información sobre cómo se discuten las diferentes condiciones en línea.
- Estos hallazgos pueden informar a los profesionales de la salud mental, la gestión de la comunidad y los esfuerzos para reducir el estigma.
Palabras clave:
salud mentalReddittransformadoresanálisis de textodescubrimiento de conocimientominería de textoprocesamiento del lenguaje naturalaprendizaje automáticoclasificación de textoexplicabilidad de la IAcomunidades en líneatrastorno bipolartrastorno límite de la personalidadansiedaddepresión
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