Overview of HOPE at IberLEF 2024Approaching Hope Speech Detection in Social Media from Two Perspectives, for Equality, Diversity and Inclusion and as Expectations

  1. García-Baena, Daniel
  2. Balouchzahi, Fazlourrahman
  3. Butt, Sabur
  4. García-Cumbreras, Miguel Ángel
  5. Tonja, Atnafu Lambebo
  6. García-Díaz, José Antonio
  7. Bozkurt, Selen
  8. Chakravarthi, Bharathi Raja
  9. Ceballos, Hector G.
  10. Valencia-García, Rafael
  11. Sidorov, Grigori
  12. Ureña-López, L. Alfonso
  13. Gelbukh, Alexander
  14. Jiménez-Zafra, Salud María
Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2024

Número: 73

Páginas: 407-419

Tipo: Artículo

DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

Este articulo presenta la segunda edición de la tarea compartida internacional sobre detección multilingüe del discurso de la esperanza, HOPE 2024, desarrollada como parte del taller IberLEF durante el congreso SEPLN 2024. Esta tarea estuvo compuesta por dos subtareas distintas: la primera de ellas se centró en la detección del discurso esperanzador en el ámbito de la Igualdad, Diversidad e Inclusión, mientras que la segunda se enfocó en las expectativas del discurso esperanzador atendiendo a dos niveles, binario y multiclase. Diecinueve equipos participaron en la competición y dieciséis enviaron sus notas de trabajo. En la primera subtarea, el equipo mejor clasificado logró una puntuación Macro F1 media de 71,61. En la segunda subtarea, los equipos líderes demostraron un rendimiento sólido con puntuaciones F1 superiores a 80,00 para la clasificación binaria y 78,00 para los entornos de clasificación multiclase.

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Fuente de los datos: Dialnet