Paper Contents
Abstract
AbstractMovie ratings are very important for figuring out how to market films, create better content, and keep audiences happy. In todays world, movies bring people together from all sorts of backgrounds, thanks to streaming platforms and tons of online data. This project dives into the IMDB dataset, which has a lot of information like ratings, genres, cast, and runtime, to study and predict how movies score with viewers. We used machine learning to investigate what makes a movie rating high or low, looking at things such as genre, how long the film is, and other details. By cleaning the data, picking the right features, and building models, we worked to predict ratings as accurately as possible. Our findings, like a slight link between shorter movies and better ratings, can help filmmakers and studios make smarter choices about what movies to make and how to promote them.
Copyright
Copyright © 2025 Yama Sai Akshay. This is an open access article distributed under the Creative Commons Attribution License.
