Twitter sentiment analysis using deep learning

Abstract

It is well established that the tweet sentiment analysis is still focused on conventional messages, such as film reviews and product reviews, while significant improvement has been made as deep learning becomes widespread, and comprehensive data sets are accessible for training (far from just emoticons and hashtags). Nevertheless, prior opinion analysis experiments typically performed on tweets, i.e. only two forms of global polarities (i.e. optimistic and negative) occur with their work/validation/test data sets. What is more, systems' judgments are not actively aligned with the specified appraisal objects. In this paper, we have discussed some deep learning approaches for twitter sentiment analysis. We also trained our model using CNN and RNN to get some good accuracy results.