EMOTION ANALYSIS ON TEXT WORDS AND SENTENCES BASED ON SVM
The analysis on text emotional inclination has received much attention from natural language processing field in recent years, which can be widely used in spam filtering,text classification, network public opinion analysis and other applications. This paper presents a method for analysing the emotions on words and sentences in Chinese texts, which focuses on solving four kinds of emotion analysis with big granule including happy, angry, sad and fear. The seed emotional words including happy, angry, sad and fear are firstly set up, and then we analyse the characteristics of emotional words and mine potential emotional words, finally we employ, support vector machine to combine the lexical, part of speech and semantic features to recognise and classify the emotions of sentences. Experiment result shows that the method is reasonable and effective when applied to emotional words and sentences recognition in evaluation task of COAE2009.
Emotional words Emotion analysis Support vector machine Feature selection
国家科技期刊平台
NSTL
万方数据
维普
