Research on Micro-blog Sentiment Polarity Classification Based on SVM

摘要：

　　The key problem to be solved in the analysis of micro-blog emotion is the micro-blog sentiment polarity classification.Based on the analysis of various factors affecting sentiment classification of micro-blog,we recognize word sentimental polarity,extract affective and weighted sentimental feature in the sentence level.Then support vector machine(SVM)classifier is used for emotion recognition and micro-blog classification.Finally,we perform the classification model with the micro-blog corpus data sets,and improve classification accuracy by calculating confidence.The experimental results verify the effectiveness of the micro-blog sentiment polarity classification model applied to the micro-blog.

关键词： micro-blog sentiment classification word polarity identification support vector machine

作者: Peiwen Chen Xiufen Fu Shaohua Teng Sui Lin Jingqiao Lu

作者单位: School of Computer,Guangdong University of Technology,Guangzhou,P.R.China

会议类型: 国际会议

会议名称: The 9th International Conference on Pervasive Computing and Application(ICPCA 2014)(第九届全国普适计算学术会议、第九届全国人机交互联合学术会议)

会议地点: 南昌

会议语种:英文

页码: 1-13

在线出版日期: 2013-09-26（万方平台首次上网日期，不代表论文的发表时间）