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Cho, K., Van Merrienboer, B., Gulcehre, C., et al. (2014) Learning Phrase Representations Using RNN Encoder-Decoder for Statistical Machine Translation. arXiv Preprint arXiv:1406.1078.
https://doi.org/10.3115/v1/D14-1179

has been cited by the following article:

• TITLE: Review of Research on Text Sentiment Analysis Based on Deep Learning

  AUTHORS: Wenling Li, Bo Jin, Yu Quan

  KEYWORDS: Deep Learning, Sentiment Analysis, Convolutional Neural Network, Recurrent Neural Network

  JOURNAL NAME: Open Access Library Journal, Vol.7 No.3, March 9, 2020

  ABSTRACT: Sentiment analysis is part of the field of natural language processing (NLP), and its purpose is to dig out the process of emotional tendencies by analyzing some subjective texts. With the development of word vector, deep learning develops rapidly in natural language processing. Therefore, the text emotion analysis based on deep learning has also been widely studied. This article is mainly divided into two parts. The first part briefly introduces the traditional methods of sentiment analysis. The second part introduces several typical methods of sentiment analysis based on deep learning. The advantages and disadvantages of sentiment analysis are summarized and analyzed, which lays a foundation for the in-depth research of scholars.