Based on the shortcomings of sentiment analysis, this paper implemented a rule-based sentiment classification method and designed a basic feature set for machine learning methods. A sentiment analysis method via a combination of rule-based and machine learning methods is proposed. An effective integration feature set is obtained by adding various rule-based features to the basic feature set after expanding and converting them. The proposed method outperforms the baseline of any single method. Finally ensemble of three different classifiers is used to make further improvement on the performance of microblog sentiment classification.