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A Comparison Between Two Spanish Sentiment Lexicons in the Twitter Sentiment Analysis Task

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Advances in Artificial Intelligence - IBERAMIA 2016 (IBERAMIA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10022))

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Abstract

Sentiment analysis aims to determine people’s opinions towards certain entities (e.g., products, movies, people, etc.). In this paper we describe experiments performed to determine sentiment polarity on tweets of the Spanish corpus used in the TASS workshop. We explore the use of two Spanish sentiment lexicons to find out the effect of these resources in the Twitter sentiment analysis task. Rule based and supervised classification methods were implemented and several variations over those approaches were performed. The results show that the information of both lexicons improve the accuracy when is provided as a feature to a Naïve Bayes classifier. Despite the simplicity of the proposed strategy, the supervised approach obtained better results than several participant teams of the TASS workshop and even the rule based approach overpass the accuracy of one team which used a supervised algorithm.

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Notes

  1. 1.

    All the words in the SEL lexicon are lemmatized.

  2. 2.

    Experimentally better results were achivied when using all the categories instead of using only the affective process category like in the rule based approach.

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Acknowledgments

We thank the support of Instituto Politécnico Nacional (IPN), ESCOM-IPN, CIC-IPN, SIP-IPN projects number 20160815, 20162058, COFAA-IPN, and EDI-IPN.

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Authors and Affiliations

  1. Instituto Politécnico Nacional, ESCOM, Av. Juan de Dios Bátiz esq. Av. Miguel Othón de Mendizábal, Col. Lindavista, Del. Gustavo A. Madero, 07738, Mexico City, Mexico

    Omar Juárez Gambino

  2. Instituto Politécnico Nacional, CIC, Av. Juan de Dios Bátiz esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Del. Gustavo A. Madero, 07738, Mexico City, Mexico

    Omar Juárez Gambino & Hiram Calvo

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  1. Omar Juárez Gambino
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  2. Hiram Calvo
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Correspondence to Omar Juárez Gambino .

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Editors and Affiliations

  1. INAOE , Tonantzintla, Mexico

    Manuel Montes y Gómez

  2. Astrofisica Optica y Electronica, INAOE , Puebla, Mexico

    Hugo Jair Escalante

  3. Universidad Nacional de Costa Rica , Heredia, Costa Rica

    Alberto Segura

  4. Universidad Nacional de Costa Rica , Heredia, Costa Rica

    Juan de Dios Murillo

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Gambino, O.J., Calvo, H. (2016). A Comparison Between Two Spanish Sentiment Lexicons in the Twitter Sentiment Analysis Task. In: Montes y Gómez, M., Escalante, H., Segura, A., Murillo, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2016. IBERAMIA 2016. Lecture Notes in Computer Science(), vol 10022. Springer, Cham. https://doi.org/10.1007/978-3-319-47955-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-47955-2_11

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