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中文文本情感分析综述
引用本文:魏韡,向阳,陈千.中文文本情感分析综述[J].计算机应用,2011,31(12):3321-3323.
作者姓名:魏韡  向阳  陈千
作者单位:1. 井冈山大学 电子与信息工程学院,江西 吉安 3430092. 同济大学 电子与信息工程学院,上海 201804
基金项目:江西省教育厅青年科学基金资助项目
摘    要:由于主观性文本有很多应用价值,情感分析近年来引起了很多研究人员的兴趣.情感分析是对主观性文本进行挖掘与分析,获取有用的知识和信息.针对中文文本情感分析的研究现状与进展进行总结.首先按粒度层次,从词语级、语句级、篇章级三个不同粒度层次细致地介绍相关的技术,再按文本的类型,分析了产品评论和新闻评论的研究进展.接着介绍了中文...

关 键 词:情感分析  情感极性  中文文本  评测  语料库
收稿时间:2011-05-04
修稿时间:2011-06-27

Survey on Chinese text sentiment analysis
WEI Wei,XIANG Yang,CHEN Qian.Survey on Chinese text sentiment analysis[J].journal of Computer Applications,2011,31(12):3321-3323.
Authors:WEI Wei  XIANG Yang  CHEN Qian
Affiliation:1. College of Electronics and Information Engineering, Jinggangshan University, Ji’an Jiangxi 343009,China2. College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
Abstract:The sentiment analysis has aroused the interest of many researchers in recent years,since the subjective texts are useful for many applications. Sentiment analysis is to mine and analyze the subjective text, aiming to acquire valuable knowledge and information. This paper surveyed the status of the art of Chinese sentiment analysis. Firstly, the technique was introduced in detail, according to different granularity levels, namely word, sentence, and document; and the research of product review and news review were presented respectively. Then evaluation and corpus for Chinese text sentiment analysis were introduced. The difficulty and trend of Chinese text sentiment analysis were concluded finally. This paper focuses on the major methods and key technologies in this field, making detailed analysis and comparison.
Keywords:sentiment analysis                                                                                                                        sentiment polarity                                                                                                                        Chinese text                                                                                                                        evaluation                                                                                                                        corpus set
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