Journal ArticleUnknown
A Deep Recurrent Neural Network with BiLSTM model for Sentiment Classification
Author Affiliations
Shahjalal University of Science and Technology
Year2018
Citations140
Abstract
In the field of sentiment classification, opinions or sentiments of the people are analyzed. Sentiment analysis systems are being applied in social platforms and in almost every business because the opinions or sentiments are the reflection of the beliefs, choices and activities of the people. With these systems it is possible to make decisions for businesses to political agendas. In recent times a huge number of people share their opinions across the Internet using Bengali. In this paper a new way of sentiment classification of Bengali text using Recurrent Neural Network(RNN) is presented. Using deep recurrent neural network with BiLSTM, the accuracy 85.67% is achieved.
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Fields & Keywords
Physical SciencesComputer ScienceArtificial IntelligenceSentiment Analysis and Opinion MiningAdvanced Text Analysis TechniquesText and Document Classification TechnologiesArtificial intelligenceMachine learningData scienceNatural language processingWorld Wide WebLawPure mathematicsProgramming language