Prediction of movie success based on machine learning and twitter sentiment analysis using internet movie database data

<span lang="EN-US">Nowadays, predicting the success of a new movie is crucial task. In this work, hybrid approach considers features as well sentiment expressed in review to predict rate movie. Multiple such title, director, star cast, and writer. Are considered for prediction. The related raw data collected from internet database (IMDb) website after pre-processing, used generate supervised machine learning model. Different models are compared one with best results further. mean squared error, root error r2 score generated comparable existing models. Further, analysis movie-related tweets performed. accuracy model 88.47%. Finally, two combined give prediction rating movies encouraging. proposed may be find top-rated particular calendar year.</span>