Comparison of Clustering Algorithms for Knowledge Discovery in Social Media PublicationsA Case Study of Mental Health Analysis

  1. Couto, Manuel
  2. Parapar, Javier
  3. Losada, David E.
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2024

Número: 73

Páginas: 69-81

Tipo: Artículo

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Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

En la era de las redes sociales, el contenido generado por los usuarios es fundamental para detectar los primeros signos de trastornos mentales. En este estudio utilizamos el agrupamiento de publicaciones por tópicos para analizar el contenido de la plataforma Reddit. Nuestro objetivo primordial es utilizar técnicas de agrupamiento para descubrir temas centrales, con un enfoque en la identificación de temas comunes entre los grupos de usuarios que sufren enfermedades mentales como la depresión, la anorexia, la adicción a los juegos de azar y las autolesiones. Nuestros hallazgos muestran que ciertos clusters son más cohesivos, por ejemplo mostrando una mayor proporción de textos de personas con depresión. Además, hemos descubierto subreddits que están fuertemente vinculados a textos escritos por usuarios deprimidos. Estos hallazgos arrojan luz sobre cómo las interacciones en línea y los temas que se tratan en los subreddits reflejan aspectos de salud mental, abriendo el camino para futuras investigaciones e intervenciones dirigidas a la prevención de trastornos.

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Fuente de los datos: Dialnet