文本情感分析综述

A Survey of Sentiment Analysis

近年来,随着互联网和社交网络的发展,网络上文本信息迅速增长,对文本情感进行分析成为研究热点。根据文本情感分析方法的不同,总结了近年来文本情感分析的研究进展。将文本情感分析分为基于词典的方法和基于机器学习的方法两大类:基于词典的文本情感分析方法分为人工构建和自动构建两种;基于机器学习的文本情感分析方法分为基于贝叶斯算法、基于最大熵算法和基于SVM的文本情感分析3种。通过梳理国内外研究现状,对两类情感分析方法进行了深入分析,对文本情感分析进行了总结和展望。

In recent years,with the development of the internet and social networks,text information on the Internet has been increased rapidly,and sentiment analysis has become a research hotspot.According to the different methods of sentiment analysis,the research progress of sentiment analysis in recent years is summarized.Sentiment analysis is divided into dictionary-based methods and machine learning-based methods.The dictionary-based sentiment analysis methods are divided into two kinds：artificial construction and automatic construction.Machine learning-based sentiment analysis methods are divided into three kinds based on Bayesian algorithm,based on maximum entropy algorithm and sentiment analysis based on SVM.Through the research status at home and abroad,two kinds of sentiment analysis methods are deeply analyzed,and the sentiment analysis is summarized and forecasted.