Toxicity in Spanish News Comments and its Relationship with Constructiveness

  1. López-Úbeda, Pilar
  2. Plaza-del-Arco, Flor Miriam
  3. Díaz-Galiano, Manuel-Carlos
  4. Martín-Valdivia, M. Teresa
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2024

Número: 73

Páginas: 43-53

Tipo: Artículo

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Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

Los comentarios en plataformas de noticias digitales constituyen una fuente esencial de información y opinión. Sin embargo, frecuentemente se transforman en focos de discurso toxico e incivilidad. La detección de la toxicidad en dichos comentarios es fundamental para comprender y atenuar este problema. Este artículo introduce un corpus de comentarios de noticias en español, etiquetados por su toxicidad (NECOS-TOX), y realiza una serie de experimentos empleando diversos algoritmos de aprendizaje automático, incluyendo modelos de lenguaje basados en la arquitectura de transformers. Los resultados obtenidos demuestran que los modelos de lenguaje específicos para el español, como BETO, poseen la capacidad de identificar la toxicidad en los comentarios de noticias en español. Adicionalmente, se exploró la relación existente entre la toxicidad y la constructividad en estos comentarios, concluyendo que no se aprecia una correlación evidente entre ambos factores. Estos hallazgos aportan luz sobre las complejidades inherentes al discurso en línea y subrayan la necesidad imperante de realizar investigaciones adicionales para comprender de manera más profunda la relación entre la toxicidad y la constructividad en los comentarios de noticias en español.

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Fuente de los datos: Dialnet