ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2018, Vol. 55 ›› Issue (1): 30-52.doi: 10.7544/issn1000-1239.2018.20170055

• 综述 • 上一篇    下一篇

文本情绪分析综述

李然1,2,林政1,林海伦1,王伟平1,孟丹1,2   

  1. 1(信息内容安全技术国家工程实验室(中国科学院信息工程研究所) 北京 100093);2(中国科学院大学网络空间安全学院 北京 100049) (liran@iie.ac.cn)
  • 出版日期: 2018-01-01
  • 基金资助: 
    国家自然科学基金项目(61502478,61602467);国家“八六三”高技术研究发展计划基金项目(2013AA013204)

Text Emotion Analysis: A Survey

Li Ran1,2, Lin Zheng1, Lin Hailun1, Wang Weiping1, Meng Dan1,2   

  1. 1(National Engineering Laboratory for Information Security Technologies (Institute of Information Engineering, Chinese Academy of Sciences), Beijing 100093);2(School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049)
  • Online: 2018-01-01

摘要: 随着社交网络、电子商务、移动互联网等技术的发展,各种网络数据迅速膨胀.互联网上蕴含着大量带有情绪色彩的文本数据,对其充分挖掘可以更好地理解网民的观点和立场.首先介绍了情绪分析的相关背景知识,包括不同情绪分类体系和文本情绪分析在舆情管控、商业决策、观点搜索、信息预测、情绪管理等场景的应用;然后从情绪分类的角度整理归纳了文本情绪分析的主流方法,并对其进行了细致的介绍和分析对比;最后,阐述了文本情绪分析存在的数据稀缺性、类别不平衡、领域依赖性、语言不平衡等问题,并结合大数据处理、多媒体融合、深度学习发展、特定主题挖掘和多语言协同等研究热点对文本情绪分析的前沿进展进行了概括和展望.

关键词: 情绪分析, 观点挖掘, 情感分析, 机器学习, 情绪词典

Abstract: With the rapid development of social networks, electronic commerce, mobile Internet and other technologies, all kinds of Web data expand rapidly. There are a large number of emotional texts on the Internet, and they are very helpful to understand the netizen’s opinion and viewpoint if fully explored. The aim of emotion classification is to predict the emotion categories of emotive texts, which is the core of emotion analysis. In this paper, we first introduce the background knowledge of emotion analysis including different emotion classification systems and its application scenarios on public opinion management and control, business decisions, opinion search, information prediction, emotion management. Then we summarize the mainstream approaches of emotion classification, and make a detailed description and analysis on these approaches. Finally, we expound the problems of data sparsity, class imbalance learning, dependence for the strong domain knowledge and language imbalance existing in the emotion analysis work. The research progress of text emotion analysis is summarized and prospect combined with large data processing, the mixing of multiple media, deep learning development, mining on a specific topic and multilingual synergy.

Key words: emotion analysis, opinion mining, sentiment analysis, machine learning, emotion lexicon

中图分类号: