文章基本信息

标题：Review of Research on Text Sentiment Analysis Based on Deep Learning
本地全文：下载
作者：Wenling Li ; Bo Jin ; Yu Quan 等
期刊名称：Open Access Library Journal
印刷版ISSN：2333-9705
电子版ISSN：2333-9721
出版年度：2020
卷号：7
期号：3
页码：1-8
DOI：10.4236/oalib.1106174
语种：English
出版社：Scientific Research Pub
摘要：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.
关键词：Deep LearningSentiment AnalysisConvolutional Neural NetworkRecurrent Neural Network