A Comprehensive Study on Various Statistical Techniques for Prediction of Movie Success
This provides insights for the film industry to forecast movie popularity and box office performance, but it is incremental as it applies existing methods to new data.
The study compared various machine learning models to predict movie success, finding that a neural network achieved the best performance with about 86% accuracy.
The film industry is one of the most popular entertainment industries and one of the biggest markets for business. Among the contributing factors to this would be the success of a movie in terms of its popularity as well as its box office performance. Hence, we create a comprehensive comparison between the various machine learning models to predict the rate of success of a movie. The effectiveness of these models along with their statistical significance is studied to conclude which of these models is the best predictor. Some insights regarding factors that affect the success of the movies are also found. The models studied include some Regression models, Machine Learning models, a Time Series model and a Neural Network with the Neural Network being the best performing model with an accuracy of about 86%. Additionally, as part of the testing data for the movies released in 2020 are analysed.