Sentiment lexicons and other linguistic knowledge proved to be beneficial in polarity classification. This paper introduces a linguistically informed Convolutional Neural Network (lingCNN), which incorporates this valuable kind of information into the model. We present two intuitive and simple methods: The first one integrates word-level features, the second sentence-level features. By combining both types of features our model achieves results that are comparable to state-of-the- art systems.
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