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Cross-Language Approach for Sentiment Classification in Brazilian Portuguese with ConvNets

  • Rafael P. da Silva
  • Flávio A. O. Santos
  • Filipe B. do Nascimento
  • Hendrik T. Macedo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 738)

Abstract

Sentiment Analysis (SA) employs Natural Language Processing (NLP) techniques in order to infer emotional states and subjective information contained in texts. Generally, previously trained machine learning models are used to identify the polarity of an opinion concerning a given target (e.g. film, book, etc.). Therefore, engineering features in order to create the training set for the learning model is a central task in SA problems. Additionally, finding properly labeled datasets for NLP models containing non-English text is a big challenge. Thus, we aim to contribute to SA in texts written in Brazilian Portuguese (PtBR) by validating the use of ConvNet, a convolutional neural network (CNN) that works with character-level inputs, in analyzing the polarity of product reviews in PtBR. The results obtained from our experiments confirm the model’s efficiency.

Keywords

Sentiment analysis Natural language processing Convolutional neural network Character level representation Linguistic corpus for PtBR 

Notes

Acknowledgements

The authors thank CAPES and FAPITEC-SE for the financial support [Edital CAPES/FAPITEC/SE No 11/2016—PROEF, Processo 88887.160994/2017-00] and LCAD-UFS for providing a cluster for the execution of the experiments. The authors also thank FAPITEC-SE for granting a graduate scholarship to Flávio Santos, CNPq for granting a graduate scholarship to Filipe Nascimento and a productivity scholarship to Hendrik Macedo [DT-II, Processo 310446/2014-7]

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Rafael P. da Silva
    • 1
  • Flávio A. O. Santos
    • 2
  • Filipe B. do Nascimento
    • 1
  • Hendrik T. Macedo
    • 2
  1. 1.Departamento de ComputaçãoUniversidade Federal de SergipeSão CristóvãoBrazil
  2. 2.Programa de Pós-Graduação em Ciência da ComputaçãoUniversidade Federal de SergipeSão CristóvãoBrazil

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