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Issue title: Special section: Selected papers of LKE 2019
Guest editors: David Pinto, Vivek Singh and Fernando Perez
Article type: Research Article
Authors: González, José Ángel*; | Hurtado, Lluís-F. | Pla, Ferran
Affiliations: VRAIN: Valencian Research Institute for Artificial Intelligence, Universitat Politècnica de València, Camí de Vera sn, 46022, València, Spain
Correspondence: [*] Corresponding author. José Ángel González, VRAIN: Valencian Research Institute for Artificial Intelligence, Universitat Politècnica de València, Camí de Vera sn, 46022, València, Spain. E-mail: jogonba2@dsic.upv.es.
Abstract: This paper describes our proposal for Sentiment Analysis in Twitter for the Spanish language. The main characteristics of the system are the use of word embedding specifically trained from tweets in Spanish and the use of self-attention mechanisms that allow to consider sequences without using convolutional nor recurrent layers. These self-attention mechanisms are based on the encoders of the Transformer model. The results obtained on the Task 1 of the TASS 2019 workshop, for all the Spanish variants proposed, support the correctness and adequacy of our proposal.
Keywords: Twitter, sentiment analysis, transformer encoders
DOI: 10.3233/JIFS-179881
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 2165-2175, 2020
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