方面级情感分析综述  

Summarization of Aspect-level Sentiment Analysis

作　　者：李阳 王石[2] 朱俊武[1] 梁明轩[1,2] 高翔 焦志翔 LI Yang;WANG Shi;ZHU Junwu;LIANG Mingxuan;GAO Xiang;JIAO Zhixiang(College of Information Engineering,Yangzhou University,Yangzhou,Jiangsu 225000,China;Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]扬州大学信息工程学院,江苏扬州225000 [2]中国科学院计算技术研究所,北京100190

出　　处：《计算机科学》2023年第S01期24-30,共7页Computer Science

基　　金：国家242信息安全计划项目(2021A008);北京市科技新星计划交叉学科合作课题(Z191100001119014);国家重点研发计划重点专项(2017YFC1700300,2017YFB1002300);国家自然科学基金(61702234);江苏省(扬州大学)研究生科研与实践创新计划项目(SJCX21_1551)。

摘　　要：情感分析是自然语言处理领域的重要分支之一。随着时代的发展,为了能从文本数据中提取出更多的情感信息,方面级情感分析在情感分析中的关注度越来越高。首先介绍方面级情感分析的背景知识、相关概念,并从方面抽取和方面情感分类两个子任务角度进行阐述。在方面抽取方面,介绍了基于相似度算法、主题模型和序列标注的相关方法。在方面情感分类方面,介绍了基于情感词典与规则、机器学习和深度学习的相关方法,并整理了方面级情感分析中常用的中英文数据集和情感字典,最后对方面级情感分析目前面临的挑战和未来的发展方向做出总结和展望。Sentiment analysis is one of the important branches of natural language processing.With the development of the times,in order to extract more sentiment information from text,aspect-level sentiment analysis is paying more and more attention in sentiment analysis.Firstly,this paper introduces the background knowledge and related concepts of aspect-level sentiment analysis,and explains it from the perspective of two subtasks of aspect extraction and aspect sentiment classification.In terms of aspect extraction,related methods based on similarity algorithms,topic models and sequence labeling are introduced.In terms of aspect sentiment classification,related methods based on sentiment lexicon and rules,machine learning and deep learning are introduced,and the Chinese and English data sets and sentiment lexicon commonly used in aspect-level sentiment analysis are sorted out.Finally,making a summary and outlook for the current challenges and future development directions of aspect-level sentiment analysis.

关 键 词：情感分析 方面抽取 方面情感分类 情感词典 深度学习 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]