Gómez-Rodríguez, CarlosImran, MuhammadVilares, DavidSolera, ElenaKellert, Olga2024-09-092024-09-092024Gómez-Rodríguez, C., Imran, M., Vilares, D., Solera, E., & Kellert, O. (2024). Dancing in the Syntax Forest: Fast, Accurate and Explainable Sentiment Analysis with SALSA. CEUR Workshop Proceedings. Vol. 3729, Pages 12 – 17. Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations, SEPLN-CEDI-PD 2024, A Coruna, June 20241613-0073http://hdl.handle.net/2183/38924Included in Proceedings of the Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations (SEPLN-CEDI-PD 2024) co-located with the 7th Spanish Conference on Informatics (CEDI 2024) A Coruña, Spain, June 19-20, 2024[Abstract]: Sentiment analysis is a key technology for companies and institutions to gauge public opinion on products, services or events. However, for large-scale sentiment analysis to be accessible to entities with modest computational resources, it needs to be performed in a resource-efficient way. While some efficient sentiment analysis systems exist, they tend to apply shallow heuristics, which do not take into account syntactic phenomena that can radically change sentiment. Conversely, alternatives that take syntax into account are computationally expensive. The SALSA project, funded by the European Research Council under a Proof-of-Concept Grant, aims to leverage recently-developed fast syntactic parsing techniques to build sentiment analysis systems that are lightweight and efficient, while still providing accuracy and explainability through the explicit use of syntax. We intend our approaches to be the backbone of a working product of interest for SMEs to use in production.engAtribución 4.0 Internacional© 2024 Copyright for this paper by its authors.http://creativecommons.org/licenses/by/3.0/es/Opinion miningParsingSentiment analysisSyntaxconference outputopen access