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Overview of FinancES 2023: Financial Targeted Sentiment Analysis in Spanish

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dc.contributor.authorAlmela, Ángela
dc.contributor.authorGarcía Díaz, José Antonio
dc.contributor.authorGarcía Sánchez, Francisco
dc.contributor.authorAlcaraz Mármol, Gema
dc.contributor.authorMarín Pérez, María José
dc.contributor.authorValencia García, Rafael
dc.contributor.departmentFilología Inglesa
dc.date.accessioned2026-02-19T09:17:30Z
dc.date.available2026-02-19T09:17:30Z
dc.date.copyright© 2023 Sociedad Española para el Procesamiento del Lenguaje Natural
dc.date.issued2023-09
dc.description.abstractThis 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.
dc.description.abstractEste 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 anáisis 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 econ´omicos), 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.
dc.formatapplication/pdf
dc.format.extent7
dc.identifier.citationProcesamiento del Lenguaje Natural, Revista nº 71, septiembre de 2023, pp. 417-423
dc.identifier.doihttps://doi.org/10.26342/2023-71-33
dc.identifier.eissn1989-7553
dc.identifier.issn1135-5948
dc.identifier.urihttp://hdl.handle.net/10201/207942
dc.languageeng
dc.publisherSociedad Española de Procesamiento del Lenguaje Natural
dc.relationThis work is part of the research project AIInFunds (PDC2021-121112-I00) funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. This work is also part of the research project LaTe4PSP (PID2019-107652RB-I00) funded by MCIN/AEI/10.13039/501100011033 and the research project LaTe4PoliticES (PID2022-138099OB-I00) funded by MCIN/AEI/10.13039/501100011033 and the European Fund for Regional Development (FEDER)-a way to make Europe.
dc.relation.publisherversionhttp://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6571/3971
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectNamed Entity Recognition
dc.subjectTargeted Sentiment Analysis
dc.subjectFinances
dc.subjectSentiment Analysis
dc.subjectAnálisis de sentimientos
dc.subjectExtracción de entidades nombradas
dc.subjectAnálisis de sentimiento dirigido
dc.subjectFinanzas
dc.subject.odsObjetivo 8: Crecimiento económico
dc.titleOverview of FinancES 2023: Financial Targeted Sentiment Analysis in Spanish
dc.title.alternativeResumen de FinancES 2023: Análisis de Sentimiento Dirigido en Español sobre Finanzas
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
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