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

Journal:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Year of publication: 2023

Issue: 71

Pages: 417-423

Type: Article

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More publications in: Procesamiento del lenguaje natural

Abstract

This paper presents the FinancES 2023 shared task, organized in the IberLEF 2023 workshop, within the framework of the 39th International Conference of the Spanish Society for Natural Language Processing (SEPLN 2023). The aim of this task is to extend the challenge of sentiment analysis in Spanish to the financial domain, in order to extract the sentiment that a piece of financial information can have for several actors, including the main economic target (i.e., the specific company or asset where the economic fact applies), other companies (i.e., the entities producing the goods and services that others consume) and consumers (i.e., households/individuals). Specifically, two tasks are proposed and evaluated separately. One to identify the main target and to determine the sentiment polarity towards such target, and a second task to assess the sentiment towards both other companies and consumers. The ranking includes results for 10 different teams proposing novel approaches, mostly based on Transformers and generative language models.

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