Artificial Intelligence

   

Sentiment Classification Over Brazilian Supreme Court Decisions Using Multi-Channel CNN

Authors: Marcus Oliveira da Silva

Sentiment analysis seeks to identify the viewpoint(s) underlying a text document; In this paper, we present the use of a multichannel convolutional neural network which, in effect, creates a model that reads text with different n-gram sizes, to predict with good accuracy sentiments behind the decisions issued by the Brazilian Supreme Court, even with a very imbalanced dataset we show that a simple multichannel CNN with little to zero hyperparameter tuning and word vectors, tuned on network training, achieves excellent results on the Brazilian Supreme Court data. We report results of 97% accuracy and 84% average F1- score in predicting multiclass sentiment dimensions. We also compared the results with classical classification machine learning models like Naive Bayes and SVM.

Comments: 11 Pages.

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Submission history

[v1] 2019-10-27 18:08:55

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