Sentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks

Juan Manuel Adán Coello; Armando  Dalla Costa Neto

doi:10.31686/ijier.vol7.iss6.1547

Authors

Juan Manuel Adán Coello

Pontifícia Universidade Católica de Campinas (PUC-Campinas) Brazil
Armando Dalla Costa Neto

PUC-Campinas

DOI:

https://doi.org/10.31686/ijier.vol7.iss6.1547

Keywords:

opinion mining, deep learning, Brazilian Portuguese

Abstract

Sentiment analysis of texts posted on Twitter is a natural language processing task whose importance has grown along with the increase in the number of users of the platform and the interest of organizations on the opinions of their employees, customers and users.Although Brazil is the sixth country in the world with most active users of Tweeter and Portuguese is the seventh most spoken language in the world, with 221 million speakers (200 million of them living in Brazil), the number of articles that discuss sentiment analysis approaches for Brazilian Portuguese is a small fraction of those that focus on the English language. On the other hand, few works use deep learning for this task when compared with other machine learning and lexical based methods. In this context, the work described in this article addresses the problem using Convolutional Neural Networks (CNN). The paper presents the results of an experimental evaluation that shows that a CNN with a relatively simple architecture can perform much better than a previous approach that uses ensembles of other machine learning classifiers combined with text preprocessing heuristics

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