Sentiment analysis

This is a classification task where the participating system can predict the polarity of an opinion in TripAdvisor issued by a tourist who traveled to the most representative places, restaurants and hotels in Mexico. Each opinion's class is an integer between [1, 5], where 1 represents the most negative polarity and 5 the most positive. 

Publication
Miguel Á. Álvarez-Carmona, Ángel Díaz-Pacheco, Ramón Aranda, Ansel Y. Rodríguez-González, Daniel Fajardo-Delgado, Rafael Guerrero-Rodríguez, Lázaro Bustio-Martínez (2022) Overview of Rest-Mex at IberLEF 2022: Recommendation System, Sentiment Analysis and Covid Semaphore Prediction for Mexican Tourist Texts. Procesamiento del Lenguaje Natural, Revista nº 69, septiembre de 2022, pp. 289-299.
Competition
Rest-Mex en IberLEF 2022: Sistema de Recomendación, Análisis de Sentimiento y Predicción de Semáforo Covid para Textos Turísticos Mexicanos
Language
Spanish
URL Task
https://sites.google.com/cicese.edu.mx/rest-mex-2022
NLP topic
sentiment analysis
Abstract task
Classification
Year
2022
Publication link
http://journal.sepln.org/sepl…
Ranking metric
Macro F1

Task results

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.