A Comparative Study on Semantic Orientation Classification of Chinese Text
Zhuo Chen · Information Security and Communications Privacy · 2010
With wide spread of the Internet in recent years, the amount of on-line reviews grows fast. Analysis on these on-line reviews and identification of the semantic orientation contained could provide important decision support for customers, enterprises and government organizations. Na.1. ve Bayesian classifier in machine learning techniques and support vector machines are adopted for the research of semantic orientation classification of Chinese text with the com-bination of different stop word list, different feature selection methods and different feature weighing assignment methods. The experimental results show that the sentiment orientation classification could obtain high performance by using stop word list-which would remain most part of speech containing semantic information, with document frequency as feature selection method and by applying support vector machines classifier based on term frequency.