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Complex Sentiment Analysis using Recursive Autoencoders

We use a machine learning framework based on recursive autoencoders to make sentence level predictions regarding the subject, object and sentiment of the sentence. Our model learns vector representations of multi-word phrases. The syntactic structure of the sentence is incorporated into our model by using the Stanford Parser tree thereby enabling it to make sentiment predictions with respect to subject, object, etc.