Implementation of Sentiment Analysis System using DLCNN based Opinion Mining

Opinion mining is the process of gathering the set of opinions from different users, which contains happy, sad, normal based different types of sentiments. However, the conventional machine learning classifiers are failed to provide the maximum sentiment classification performance. Therefore, this article is focused on implementation of deep learning convolutional neural network (DLCNN) system for sentiment analysis and classification. Here, DLCNN model is used to extract the deep features from dataset, which identifies the relationship between different sentiments. The simulations conducted on twitter dataset shows that the proposed method resulted in superior performance as compared to existing models.