FinancES: Financial sentiment analysis at document level for companies and consumers

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 determining the sentiment polarity of each news headline towards both companies and consumers.

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
UNAM Text Mining 0.3704
LLI-UAM 0.6423
Team ITST 0.2482
SINAI 0.6349
ABCD Team 0.6103
abc111 0.5750
fanchuyi 0.4726
Ankit Singh Raikuni 0.4576
NLP_URJC 0.4251

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.