The social networks and the rapid development of new technologies have led to
considerable changes in the tourism industry. Artificial intelligence, in particular natural …

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 …

In the context of a globalized world where travel enthusiasts seek personalized
recommendations for their favourite destinations, the study delves into sentiment analysis …

The problem of sentiment analysis of tourism data focuses on the analysis of the multimodal
characteristics of the data generated digitally by tourists on each platform or social network …

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 …

Every day millions of people express their opinions, suggestions and views about
accommodation, services, and tourist destinations on the web and online applications. The …

This article presents a proposal for the treatment of an unbalanced tourist database with
emphasis on minority classes for its classification, in this case, one based on BERT, called …

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 …

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

This paper shows the Arandanito team proposal for the Rest-Mex 2023 and examines the
role of verbs, nouns, and adjectives in analyzing tourist opinions in Spanish. We employ …