摘要
提出了构建基于HowNet和SentiWordNet的中文情感词典方法。将词语自动分解为多个义元后计算其情感倾向强度,并且使用词典校对方法对词语情感倾向强度进行优化。将所构建词典应用到文本情感分析任务中,使用支持向量机构建文本情感分类器进行实验。实验结果表明,该词典优于一般极性情感词典,为情感分析研究提供了有效的词典资源。
A method on building Chinese sentiment lexicon based on HowNet and SentiWordNet was proposed,in which sentiment intensity of the word was automatically calculated by decomposing it into multiple semantic units and a lexicon proofreading technique was used to optimize the value of sentiment intensity of the word. The building lexicon was applied to the task of sentiment analysis, in which the support vector machine was used to build the sentiment classifier. The experiment results showed that the built sentiment lexicon was more effective than the general polar sentiment lexi- con, and provided an effective dictionary resource for the research of sentiment analysis.
出处
《山东大学学报(工学版)》
CAS
北大核心
2013年第6期27-33,共7页
Journal of Shandong University(Engineering Science)
基金
国家社科基金资助项目(12BYY045)
教育部人文社会科学研究青年资助项目(10YJCZH247)
广东省科技计划资助项目(2010B031000014)
关键词
情感词典
情感强度
支持向量机
情感分析
中文文本
sentiment lexicon
sentiment intensity
support vector machine
sentiment analysis
Chinese text