A Deep Learning Approach for Sentiment Prediction Using LSTM Networks

The objective of sentiment analysis is to discover the positive and negative reviews. Hotel reviews have been analyzed in this paper, we have developed a binary text classifier. To prepare the data for the text classifier, we employ several natural language processing (NLP) preprocessing techniques and rely on LSTM layers. There are more than 38932 data samples in the dataset, split evenly between good and negative comments on the hotel’s services and general atmosphere. A situation’s underlying perspective or sentiment can be uncovered with the use of sentiment analysis. Understanding the tone or motivation of a message through text, audio, or any other medium. Text analysis and natural language processing (NLP) technologies are used to determine the potential subjectivity of data. In order to classify and work with the data more easily, we need to detect, extract, and measure such details from the text.