Using Sentiment Orientation Features for Mood Classification in Blogs

摘要：

In this paper we explore the task of mood classification for blog postings. We propose a novel approach that uses the hierarchy of possible moods to achieve better results than a standard machine learning approach. We also show that using sentiment orientation features improves the performance of classification. We used the Livejournal blog corpus as a dataset to train and evaluate our method.

关键词： Sentiment Orientation Classification Hierarchy Mood Blog

作者: Fazel KESHTKAR Diana Inkpen

作者单位: School of Information Technology and Engineering University of Ottawa, Ottawa, ON, K1N6N5, Canada

会议类型: 国际会议

会议名称: International Conference on Natural Language Processing and Knowledge Engineering(IEEE自然语言处理与知识工程国际会议 IEEE NLP-KE 2009)

会议地点: 大连

会议语种:英文

页码: 1-6

在线出版日期: 2009-09-24（万方平台首次上网日期，不代表论文的发表时间）