LSTM Based Approach for Classifying Twitter Posts for Movie Success Prediction

Social media like Twitter contains rich information about people's preferences. There is a struggle to determine how to effectively utilize and interpret those data. Models are created using these large quantities of data to predict the behavior and tendencies. People share their thoughts about movies on Twitter. The movie industry has been a very important sector in the global market. So, it is important to maximize the profit by predicting the success of the movie. In this study, we proposed an approach to classify twitter posts predict the success of movies using Long short-term memory based approach. Our approach outperformed the existing approach by obtaining 83.97% accuracy.