FinancES: Financial targeted sentiment analysis

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). The task consists on identifying the main economic target from financial news headlines and determining the sentiment polarity (positive, neutral or negative) towards such target. 

Publication
José Antonio Garcia-Díaz, Ángela Almela, Francisco García-Sánchez, Gema Alcaraz-Mármol, María José Marín, Rafael Valencia-García (2023) Overview of FinancES 2023: Financial Targeted Sentiment Analysis in Spanish. Procesamiento del Lenguaje Natural, Revista nº 71, septiembre de 2023, pp. 417-423.
Language
Spanish
NLP topic
Abstract task
Dataset
Year
2023
Ranking metric
Macro F1

Task results

System MacroF1
Ankit Singh Raikuni 0.5542
UTB-NLP 0.5292
NLP_URJC 0.5144
Team ITST 0.2769
abc111 0.7922
UNAM Text Mining 0.1346
LLI-UAM 0.7921
ABCD Team 0.7821
SINAI 0.7780

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.