Sentiment Classification Using a Single-Layered BiLSTM Model

Sentiment Classification Using a Single-Layered BiLSTM Model

This study presents a computationally efficient deep learning model for binary sentiment classification, which aims to decide the sentiment polarity of people's opinions, attitudes, and emotions expressed in written text. To achieve this, we exploited three widely practiced datasets based on pu...

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Bibliographic Details
Main Authors:	Zabit Hameed, Begonya Garcia-Zapirain
Format:	Article
Language:	English
Published:	IEEE 2020-01-01
Series:	IEEE Access
Subjects:	Bidirectional long short-term memory deep learning long-term dependencies natural language processing sentiment analysis
Online Access:	https://ieeexplore.ieee.org/document/9069952/

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