Choudhury, Najeefa NikhatMohammad, TasinIslam, Maliha BintaJamal, Humayra Binte2025-01-192025-01-19©20242024ID 20341021ID 20101587ID 20101591http://hdl.handle.net/10361/25211Cataloged from PDF version of thesis.Includes bibliographical references (pages 38-39).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.The movie industry is one of the most highly competitive and profitable businesses in the entertainment world, where predicting a movie’s success or failure of a film is a difficult task. Along with the movie trailer, key factors such as - the popularity of actors and actresses, comments, ratings, marketing budgets, critical receptions, likes, and dislikes play a significant role in determining a movie’s box office performance. Day by day, the use of social media is increasing. People express their opinions and feelings about anything on social media platforms such as Facebook, Instagram, Twitter, and YouTube. This research paper aims to predict movie box office success using opinions expressed in comments on movie trailers and Wikipedia data through the use of machine learning algorithms.47 pagesenBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.PredictionMovie box office successYouTube trailer commentsWeb scrapingMachine learningMachine learning.Youtube.Thesis