Deep Learning for Sentiment Analysis Based on Customer Reviews

Online reviews became popular as people are taking decisions with the help of them. In this context, the purpose of this project is to develop a deep learning based framework that can be used to classify customer reviews into positive or negative. This process is known as sentiment analysis. It is based on the supervised learning mechanisms where a classifier is built with knowledge of training data and then it is used to classify testing data. A prototype application is built to demonstrate proof of the concept. The success of deep learning highly relies on the availability of large-scale training data. A novel deep learning framework for review sentiment classification which employs prevalently available ratings as weak supervision signals. An algorithm by name Deep Learning based Sentiment Analysis (DLSA) is proposed and implemented to achieve this. A deep learning framework is proposed and implemented. A prototype application is built to demonstrate proof of the concept. The empirical study revealed that the proposed system is better than the state of the art.