所属单位：

信息科学技术学院

发表刊物：

Application and techniques in information security

项目来源：

国家自然科学基金项目

摘要：

Mining opinions and sentiment from cross-cultural communication Web sites can deepen mutual understanding among people between countries and provides an important channel for researching China’s cross-cultural communication. The sentiment analysis in the context of cross-cultural communication faces the challenges of culture-dependent, ne-grained sentiment understanding, and topic-centralization. Traditional approaches use machine learning methods, such as Naive Bayes, maximum entropy and support vector machine. In this paper, we exploit the machine learning methods in the context of cross-cultural communication, take the advantages of Naive Bayes and support vector machine methods and propose a novel NB-SVM based sentiment analysis algorithm. Extensive experiments show that the proposed approach performs well and can achieve 0:3% error rate of sentiment classification with appropriate parameter settings.

论文类型：

论文集

卷号：

315-326

字数：

10000

是否译文：

否

发表时间：

2015-11-30

第一作者：

徐月梅

合写作者：

wangzihou,chenyuji