Real-Time Movie Popularity Tracker Using Online Audience Reviews

The popularity of a film relies heavily on its appeal to audiences. Conventional measures of popularity, including box office sales and critical ratings, do not reflect real-time information about audience perception. This paper introduces a real-time film popularity monitor that gathers and processes online viewer reviews from sources such as YouTube. The system measures audience engagement by analysing the rate and type of comments, categorizing them into various buckets, and calculating a popularity score ranging from 1 to 10. By combining machine learning modelling with language processing algorithms, this tracker offers a real-time, live measure of a film's popularity. The increasing ability of the internet to influence audience opinion has made real-time measurement of popularity an essential tool for the movie industry. Unlike the conventional popularity measures that are derived from lagged box office figures or critic ratings, this system leverages audience discussions and engagement patterns to provide real-time insight into a movie's acceptance.