This paper presents an ensemble learning method for sentiment classification of reviews. The diversity among the machine learning algorithms for sentiment classification with different settings, which includes different features, different weight measures and the modeling of negation, is investigated in three domains, which gives a space for improving the performance. Then the ensemble learning framework, stacking generalization is introduced based on different algorithms with different settings, and compared with the majority voting. According to the characteristic of reviews, the opinion sum...
