Sentiment Analysis in the Rest-Mex Challenge

Jessica Alejandra Castillo-Montoya; Jonathan Fernando Gómez-Pérez; Tania Rosales-Onofre; Marco Antonio Torres-López; Omar J. Gambino

doi:10.1007/978-3-031-19496-2_11

Sentiment Analysis in the Rest-Mex Challenge

Jessica Alejandra Castillo-Montoya, Jonathan Fernando Gómez-Pérez, Tania Rosales-Onofre, Marco Antonio Torres-López, Omar J. Gambino

Escuela Superior de Cómputo (ESCOM)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we describe our participation in the Rest-Mex 2022 forum for the Sentiment Analysis task. The objective of the task was to create a model capable of predicting the polarity of the sentiment expressed by a tourist’s opinion, as well as the type of attraction visited. For this task, we followed two different approaches: a lexicon-based approach and a Machine Learning approach. In the lexicon-based approach, we use a dictionary with words that have a numerical value that specifies the association with some emotions or attractions. We trained a logistic regression model for the Machine Learning approach to predict sentiment polarity and attractions. Our proposal obtained a combined score for both tasks of 0.85, which is only 0.03 away from the best reported result.

Original language	English
Title of host publication	Advances in Computational Intelligence - 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Proceedings
Editors	Obdulia Pichardo Lagunas, Bella Martínez Seis, Juan Martínez-Miranda
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	137-147
Number of pages	11
ISBN (Print)	9783031194955
DOIs	https://doi.org/10.1007/978-3-031-19496-2_11
State	Published - 2022
Event	21st Mexican International Conference on Artificial Intelligence, MICAI 2022 - Monterrey, Mexico Duration: 24 Oct 2022 → 29 Oct 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13613 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st Mexican International Conference on Artificial Intelligence, MICAI 2022
Country/Territory	Mexico
City	Monterrey
Period	24/10/22 → 29/10/22

Keywords

Emotion lexicon
Machine learning
Sentiment analysis

Access to Document

10.1007/978-3-031-19496-2_11

Cite this

Castillo-Montoya, J. A., Gómez-Pérez, J. F., Rosales-Onofre, T., Torres-López, M. A., & Gambino, O. J. (2022). Sentiment Analysis in the Rest-Mex Challenge. In O. Pichardo Lagunas, B. Martínez Seis, & J. Martínez-Miranda (Eds.), Advances in Computational Intelligence - 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Proceedings (pp. 137-147). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13613 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-19496-2_11

Castillo-Montoya, Jessica Alejandra ; Gómez-Pérez, Jonathan Fernando ; Rosales-Onofre, Tania et al. / Sentiment Analysis in the Rest-Mex Challenge. Advances in Computational Intelligence - 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Proceedings. editor / Obdulia Pichardo Lagunas ; Bella Martínez Seis ; Juan Martínez-Miranda. Springer Science and Business Media Deutschland GmbH, 2022. pp. 137-147 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper, we describe our participation in the Rest-Mex 2022 forum for the Sentiment Analysis task. The objective of the task was to create a model capable of predicting the polarity of the sentiment expressed by a tourist{\textquoteright}s opinion, as well as the type of attraction visited. For this task, we followed two different approaches: a lexicon-based approach and a Machine Learning approach. In the lexicon-based approach, we use a dictionary with words that have a numerical value that specifies the association with some emotions or attractions. We trained a logistic regression model for the Machine Learning approach to predict sentiment polarity and attractions. Our proposal obtained a combined score for both tasks of 0.85, which is only 0.03 away from the best reported result.",

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Castillo-Montoya, JA, Gómez-Pérez, JF, Rosales-Onofre, T, Torres-López, MA & Gambino, OJ 2022, Sentiment Analysis in the Rest-Mex Challenge. in O Pichardo Lagunas, B Martínez Seis & J Martínez-Miranda (eds), Advances in Computational Intelligence - 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13613 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 137-147, 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Monterrey, Mexico, 24/10/22. https://doi.org/10.1007/978-3-031-19496-2_11

Sentiment Analysis in the Rest-Mex Challenge. / Castillo-Montoya, Jessica Alejandra; Gómez-Pérez, Jonathan Fernando; Rosales-Onofre, Tania et al.
Advances in Computational Intelligence - 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Proceedings. ed. / Obdulia Pichardo Lagunas; Bella Martínez Seis; Juan Martínez-Miranda. Springer Science and Business Media Deutschland GmbH, 2022. p. 137-147 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13613 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Castillo-Montoya, Jessica Alejandra

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AU - Rosales-Onofre, Tania

AU - Torres-López, Marco Antonio

AU - Gambino, Omar J.

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AB - In this paper, we describe our participation in the Rest-Mex 2022 forum for the Sentiment Analysis task. The objective of the task was to create a model capable of predicting the polarity of the sentiment expressed by a tourist’s opinion, as well as the type of attraction visited. For this task, we followed two different approaches: a lexicon-based approach and a Machine Learning approach. In the lexicon-based approach, we use a dictionary with words that have a numerical value that specifies the association with some emotions or attractions. We trained a logistic regression model for the Machine Learning approach to predict sentiment polarity and attractions. Our proposal obtained a combined score for both tasks of 0.85, which is only 0.03 away from the best reported result.

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PB - Springer Science and Business Media Deutschland GmbH

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Y2 - 24 October 2022 through 29 October 2022

ER -

Castillo-Montoya JA, Gómez-Pérez JF, Rosales-Onofre T, Torres-López MA, Gambino OJ. Sentiment Analysis in the Rest-Mex Challenge. In Pichardo Lagunas O, Martínez Seis B, Martínez-Miranda J, editors, Advances in Computational Intelligence - 21st Mexican International Conference on Artificial Intelligence, MICAI 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 137-147. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-19496-2_11