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Semantic Representations of Words and Automatic Keywords Extraction for Sentiment Analysis of Tourism Reviews

In this paper, we describe the methods used to submit our results to the Rest-Mex Sentiment Analysis task of the Iberian Languages Evaluation Forum 2021. Our contribution is twofold. Firstly, we propose an unsupervised method for keyword extraction, in order to construct a list of prototypical words conveying a sentiment weight (pre-score). Secondly, we substantially improved a scoring system previously proposed by us. We emphasize here the match of the pre-scores of prototypical words with the labels of the texts where they appear. The classification task is done by a SVM applied to vector representations of text entities. These vectors are obtained as a partial mean of word representations, selecting the words with the highest absolute value of the score in each text entity.