《计算机应用》唯一官方网站 ›› 2022, Vol. 42 ›› Issue (4): 1011-1020.DOI: 10.11772/j.issn.1001-9081.2021071262

• CCF第36届中国计算机应用大会 (CCF NCCA 2021) •    

自然语言处理在文本情感分析领域应用综述

王颖洁1, 朱久祺1, 汪祖民1, 白凤波2,3(), 弓箭3   

  1. 1.大连大学 信息工程学院,辽宁 大连 116622
    2.中国政法大学 证据科学研究院,北京 100088
    3.中科金审(北京)科技有限公司 自然语言处理部,北京 100088
  • 收稿日期:2021-07-16 修回日期:2021-08-22 接受日期:2021-08-25 发布日期:2022-04-28 出版日期:2022-04-10
  • 通讯作者: 白凤波
  • 作者简介:王颖洁(1977—),女,黑龙江齐齐哈尔人,副教授,博士,CCF会员,主要研究方向:人工智能、软件工程
    朱久祺(1997—),男(彝族),云南楚雄人,硕士研究生,CCF会员,主要研究方向:深度学习、自然语言处理
    汪祖民(1975—),男,河南信阳人,教授,博士,CCF会员,主要研究方向:人工智能、物联网
    弓箭(1994—),男,山西临汾人,主要研究方向:机器学习、自然语言处理。
  • 基金资助:
    大连大学博士专项基金资助项目(2021QL09)

Review of applications of natural language processing in text sentiment analysis

Yingjie WANG1, Jiuqi ZHU1, Zumin WANG1, Fengbo BAI2,3(), Jian GONG3   

  1. 1.College of Information Engineering,Dalian University,Dalian Liaoning 116622,China
    2.Institute of Evidence Law and Forensic Science,China University of Political Science and Law,Beijing 100088,China
    3.Natural Language Processing Technology Department,Sino FAS (Beijing) Technology Company Limited,Beijing 100088,China
  • Received:2021-07-16 Revised:2021-08-22 Accepted:2021-08-25 Online:2022-04-28 Published:2022-04-10
  • Contact: Fengbo BAI
  • About author:WANG Yingjie, born in 1977, Ph.D., associate professor. Her research interests include artificial intelligence, software engineering.
    ZHU Jiuqi, born in 1997, M. S. candidate. His research interests include deep learning, natural language processing.
    WANG Zumin, born in 1975, Ph. D., professor. His research interests include artificial intelligence, Internet of things.
    GONG Jian, born in 1994. His research interests include machine learning, natural language processing.
  • Supported by:
    Doctoral Special Fund of Dalian University(2021QL09)

摘要:

文本情感分析已经逐渐成为自然语言处理(NLP)的重要内容,并在系统推荐、用户情感信息获取,为政府、企业提供舆情参考等领域越来越占据重要地位。通过文献调研的方式,对情感分析领域的方法进行对比和综述。首先,从时间、方法等维度对情感分析的方法进行文献调研;然后,对情感分析的主要方法、应用场景进行归纳总结和对比;最后,在此基础上分析每种方法的优缺点。根据分析结果可以知道,在面对不同的任务场景,主要有三种情感分析的方法:基于情感字典的情感分析法、基于机器学习的情感分析法和基于深度学习的情感分析法,基于多策略混合的方法成为改进的趋势。文献调研表明,文本情感分析的技术方法还有改进的空间,在电子商务、心理治疗、舆情监控方面有较大市场和发展前景

关键词: 自然语言处理, 情感分析, 情感字典, 机器学习, 深度学习

Abstract:

Text sentiment analysis has gradually become an important part of Natural Language Processing(NLP) in the fields of systematic recommendation and acquisition of user sentiment information, as well as public opinion reference for the government and enterprises. The methods in the field of sentiment analysis were compared and summarized by literature research. Firstly, literature investigation was carried out on the methods of sentiment analysis from the dimensions of time and method. Then, the main methods and application scenarios of sentiment analysis were summarized and compared. Finally, the advantages and disadvantages of each method were analyzed. According to the analysis results, in the face of different task scenarios, there are mainly three sentiment analysis methods: sentiment analysis based on emotion dictionary, sentiment analysis based on machine learning and sentiment analysis based on deep learning. The method based on multi-strategy mixture has become the trend of improvement. Literature investigation shows that there is still room for improvement in the techniques and methods of text sentiment analysis, and it has a large market and development prospects in e-commerce, psychotherapy and public opinion monitoring.

Key words: Natural Language Processing (NLP), emotional analysis, emotional dictionary, machine learning, deep learning

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