Overview of FinancES 2023Financial Targeted Sentiment Analysis in Spanish

  1. Marín, María José 1
  2. Valencia García, Rafael
  3. García-Díaz, José Antonio
  4. Almela Sánchez-Lafuente, Ángela
  5. García-Sánchez, Francisco
  6. Alcaraz Mármol, Gema
  1. 1 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

Revista:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Año de publicación: 2023

Número: 71

Páginas: 417-423

Tipo: Artículo

DIALNET GOOGLE SCHOLAR lock_openRUA editor

Otras publicaciones en: Procesamiento del lenguaje natural

Resumen

Este artículo resume la tarea FinancES 2023, organizada en el taller IberLEF 2023, dentro del marco de la 39ª Conferencia Internacional de la Sociedad Española de Procesamiento del Lenguaje Natural (SEPLN 2023). El objetivo de esta tarea es mejorar la materia de la minería de opiniones en español dentro del ámbito financiero realizando el análisis de sentimientos desde distintos puntos de vista. En concreto, se proponen y estudian dos tareas que son evaluadas de forma independiente. La primera tarea consiste en (i) identificar el actor principal asociado a una noticia financiera, y (ii) el sentimiento expresado hacia dicho actor. La segunda tarea consiste en determinar el sentimiento de la noticia (i) hacia otras empresas (i.e., otros agentes económicos), y (ii) hacia los consumidores (i.e., la sociedad). El ranking incluye los resultados de 10 equipos diferentes que proponen enfoques novedosos, en su mayoría basados en Transformers y modelos generativos del lenguaje.

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Fuente de los datos: Dialnet