计算机工程Issue(4)：171-175,5.DOI:10.3969/j.issn.1000-3428.2015.04.032
基于图模型和多分类器的微博情感倾向性分析
Emotional Orientation Analysis of Microblog Based on Graph Model and Multiple Classifiers
摘要
Abstract
For the further research of the function of emotional words on emotional analysis and the improvement of microblog emotional analysis method,this paper proposes a research approach to construct emotional words graph model using relations between emotional words. The emotional value of appraisal calculated by PageRank algorithm and trained as the feature of conditional random field model so as to forecast the tendency of emotional words in specific situations, through which subjectivity classification and emotional tendency analysis of microblog can be made when integrated with Support Vector Machine(SVM) model. Experimental results show that emotional lexicon constructed by graph model enhances accuracy of the prediction of emotional word in specific situations which is also helpful for subjectivity classification and emotional tendency analysis of mircroblog.关键词
图模型/情感词/条件随机场/支持向量机/网页排序算法/倾向性分析Key words
graph model/emotional words/condition random field/Support Vector Machine ( SVM )/PageRank algorithm/orientation analysis分类
信息技术与安全科学引用本文复制引用
黄挺,姬东鸿..基于图模型和多分类器的微博情感倾向性分析[J].计算机工程,2015,(4):171-175,5.基金项目
国家自然科学基金资助重点项目(61133012) （61133012）
国家自然科学基金资助面上项目(61173062)。 （61173062）
