Applying sentiment analysis on Spanish tweets using BETO
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/356656
Tipus de documentText en actes de congrés
Data publicació2021
EditorCEUR-WS.org
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement 4.0 Internacional
Abstract
Emotion analysis of messages using machine learning techniques is a difficult and cumbersome task requiring a major effort to obtain reliable results. This challenge is even more pronounced when the target language is not English, but Spanish. To overcome this challenge, this paper describes how UPC Team applied sentiment analysis on social media messages (in particular, on Twitter) written in Spanish and, related to events that took place in April 2019 from different domains. To this aim, we present a machine learning model based on BERT and describe the results obtained to reach an accuracy of 65% approx. and the 12th position in the ranking, for this second edition of the contest for emotion detection of Spanish tweets EmoEva-lEs@IberLEF2021.
CitacióDe Arriba, A.; Oriol, M.; Franch, X. Applying sentiment analysis on Spanish tweets using BETO. A: Iberian Languages Evaluation Forum. "Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2021): co-located with the Conference of the Spanish Society for Natural Language Processing (SEPLN 2021), XXXVII International Conference of the Spanish Society for Natural Language Processing: Málaga, Spain, September, 2021". CEUR-WS.org, 2021, p. 1-8. ISSN 1613-0073.
ISSN1613-0073
Versió de l'editorhttp://ceur-ws.org/Vol-2943/emoeval_paper9.pdf
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