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An Ensemble Model for Sentiment Analysis

Sentiment analysis is to abstract sentiment polarity, positive or negtive from text. Nowadays reasearchers have proposed many models. However, the existing researches ignore the potential of ensemble model in sentiment analysis, and don't consider the application of ensemble model in sentiment analysis. This paper proposes an ensemble model for sentiment analysis, which firstly uses the word2vec model to convert the text into a matrix, then uses CNN to extract local features, and combine with LSTM to improve the accuracy of the analysis. Experimental results on the bechmark dataset show that our proposed method delivers significant improvements compared with the baselines on the task of sentiment analysis.