Purpose This study aims to present a framework for automatically collecting, cleaning and
analyzing text (news articles, in this case) to provide valuable decision-making information …

This paper presents the framework and results of the Rest-Mex task at IberLEF 2023,
focusing on sentiment analysis and text clustering of tourist texts. The study primarily focuses …

This paper presents the framework and results from the Rest-Mex task at IberLEF 2022. This
task considered three tracks: Recommendation System, Sentiment Analysis and Covid …

Chinese characters are generally correlated with their semantic meanings, and the structure
of radicals, in particular, can be a clear indication of how characters are related to each …

In this study, we developed a single Beto classification model capable of predicting 45
different classes that describes the polarity, type, and country of tourist opinions in Spanish …

Sentiment analysis and thematic unsupervised classification of tourist texts have gained
importance in recent years. Rest-Mex 2023 proposes two tasks: sentiment analysis and …

Sentiment analysis is one of the coveted areas of Natural Language Processing due to its
business application with a scope that covers any type of opinion based text. In this paper …

This paper addresses the challenge of enriching a Spanish sentiment analysis corpus with
minority instances. Existing sentiment analysis resources for Spanish suffer from a …

In this paper, we describe the methods used to submit our results to the Rest-Mex Sentiment
Analysis of the Iberian Languages Evaluation Forum 2022. The addressed challenge …

This article presents a proposal for author attribute profiling, specifically focusing on gender,
profession, and political ideology (both binary and multiclass), using a BETO (transformer …