Open AccessSentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks
Author(s) -
Juan Manuel Adán Coello,
Armando Dalla Costa Neto
Publication year - 2019
Language(s) - English
DOI - 10.31686/ijier.vol7.iss6.1547
Subject(s) - computer science , sentiment analysis , convolutional neural network , artificial intelligence , heuristics , natural language processing , portuguese , task (project management) , preprocessor , context (archaeology) , focus (optics) , artificial neural network , deep learning , machine learning , linguistics , geography , philosophy , physics , management , archaeology , optics , economics , operating system
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