短文本情感分析研究综述

A Review of Research on Short Text Sentiment Analysis

短文本情感分析是自然语言处理领域的一个重要分支,通常是把文本的主观情感进行两级或者三级分类,主要的分析研究方法有:情感词典法、机器学习法。目前国内外对于文本情感的分析研究方法比较分散、研究领域较多,不能很好地进行对比分析,根据目前的研究现状,以短文本情感分析的研究方法为视角,综合梳理了该领域的相关文献并在一定程度上做出了评述,提出了未来短文本情感分析的发展趋势和研究方向。

Short text sentiment analysis is an important branch in the field of natural language processing,which usually categorizes the subjective emotions of text into two or three levels.The main analysis and research methods include sentiment dictionary method and machine learning method.At present,the analysis and research methods related to text sentiment at home and abroad are relatively scattered and have many research fields,which cannot be well compared and analyzed.Based on the current research status,this article takes the research methods of short text sentiment analysis as the perspective,comprehensively reviews the relevant literature in this field,and proposes the development trend and research direction of future short text sentiment analysis to a certain extent.