Participation of ESCOM's Data Science Group at Rest-Mex 2022: Sentiment Analysis Task

Julian Alcibar-Zubillaga, Yanina De-Luna Ocampo, Isaias Pacheco-Castillo, Kevin Ramirez-Mendez, Juan Pablo Minoru Sainz-Takata, Omar Juárez Gambino

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

In this paper we describe the participation of the ESCOM Data Science group in Rest-Mex 2022 for the Sentiment Analysis task. For this task, 5 levels of polarity (1-5) as well as the type of attraction (restaurant, hotel and attraction) on which the opinion is given must be predicted. We followed a supervised approach using machine learning methods to train a model and then use it to make predictions. The model was tuned and tested with different text representations and obtained a combined score from both tasks of 0.84, which is only 0.5 points away from the best result.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume3202
StatePublished - 2022
Event2022 Iberian Languages Evaluation Forum, IberLEF 2022 - A Coruna, Spain
Duration: 20 Sep 2022 → …

Keywords

  • Feature Selection
  • Machine Learning
  • Sentiment Analysis

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