Browsing by Author "Muhammad Abdullah, Awais Amin and Malik Muhammad Zain Qamar"

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    Movie business predictor
    (UMT, Lahore, 2024) Muhammad Abdullah, Awais Amin and Malik Muhammad Zain Qamar
    The Movie Business Predictor project intends to revolutionize the industry using cutting edge data analytics and machine learning in order to predict how well films will do at the box office. At a time when the strategy and performance of marketing before release is key to garnering audience attention from week to week at the theatrical box office, accurate predictions can provide producers, distributors and financiers with invaluable intel. The predictive model is driven by massive data sets that include inputs like category, cast, budget… you name it (category has 52 levels!), in addition to marketing spend and release date. It then applies sophisticated algorithms to study historical trends and patterns. The model forecasts are extremely accurate since using regulation and classification algorithms, plus key variables to forecast, extracts valuable data which can in turn assist stakeholders on their strategy decisions. The project also explores the possibility of integrating sentiment analysis of social media and online platforms in order to include audience engagement, expectation etc. into real-time predictions for better model accuracy levels; The purpose of the initiative is to strengthen resource efficiency, financial security and sustainability of this challenging industry with predictive analysis based on big data.