A Sentiment Analysis System Based on Deep Learning

Abstract This application focuses on a sentiment analysis system based on deep learning, a process which consists of analysis, processing, classification and induction to subjective texts with emotional prone. Firstly, it conducts some imperative preparation for the emotional text such as cleaning up all html link, symbol and punctuation before we divide sentences into words and then turn these words into words list in order to help sorting different emotion data by using Natural Language Toolkit (NTLK) model. After the preprocessing, the data is already transferred to a network, whose framework and operation is carefully devised. Then, the network is fed with enough training data to train and adjust the model which just trained. Now the network is tested with random testing data and evaluated by its prediction accuracy. This application can show its value in a broad scope of sentiment analysis such as product evaluation and film review. It is also a remarkable application making it convenient ...