Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (12): 11-24.DOI: 10.3778/j.issn.1002-8331.2101-0022

Previous Articles     Next Articles

Review of Text Sentiment Analysis Methods

WANG Ting, YANG Wenzhong   

  1. 1.Key Laboratory of Software Engineering Technology, College of Software, Xinjiang University, Urumqi 830046, China
    2.College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
  • Online:2021-06-15 Published:2021-06-10

文本情感分析方法研究综述

王婷,杨文忠   

  1. 1.新疆大学 软件学院 软件工程技术重点实验室,乌鲁木齐 830046
    2.新疆大学 信息科学与工程学院,乌鲁木齐 830046

Abstract:

Text sentiment analysis is an important branch of natural language processing, which is widely used in public opinion analysis and content recommendation. It is also a hot topic in recent years. According to different methods used, it is divided into sentiment analysis based on emotional dictionary, sentiment analysis based on traditional machine learning, and sentiment analysis based on deep learning. Through comparing these three methods, the research results are analyzed, and the paper summarizes the advantages and disadvantages of different methods, introduces the related data sets and evaluation index, and application scenario, analysis of emotional subtasks is simple summarized. The future research trend and application field of sentiment analysis problem are found. Certain help and guidance are provided for the researchers in the related areas.

Key words: sentiment analysis, emotional dictionary, machine learning, deep learning, attention mechanism, pre-training

摘要:

文本情感分析是自然语言处理领域的一个重要分支,广泛应用于舆情分析和内容推荐等方面,是近年来的研究热点。根据使用的不同方法,将其划分为基于情感词典的情感分析方法、基于传统机器学习的情感分析方法、基于深度学习的情感分析方法。通过对这三种方法进行对比,分析其研究成果,并对不同方法的优缺点进行归纳总结,介绍相关数据集和评价指标及应用场景,对情感分析子任务进行简单概括,发现将来的情感分析问题的研究趋势及应用领域,并为研究者在相关领域方面提供一定的帮助和指导。

关键词: 情感分析, 情感词典, 机器学习, 深度学习, 注意力机制, 预训练