Revenue Predictor for Hollywood Movies using Sentiment Analysis and Regression
Journal: International Journal of Science and Research (IJSR) (Vol.10, No. 11)Publication Date: 2021-11-05
Authors : Moraish Kapoor; Karshni Mitra; Abhilash Arun;
Page : 108-114
Keywords : Language Processing; NLP; Machine Learning; ML; User interface; UI; Application Programming Interface; API;
Abstract
In today's world, data is being generated faster than ever. A vast amount of this data is freely available on social media. The main goal of data mining and analysis is to utilise this excess, unstructured data to gain insights that an industry can benefit from. The global box office value of the Hollywood movie industry was about $42.2 billion in 2019. Through this project, we aim to predict the revenue of movies on their opening weekend using sentiment analysis on Twitter data to assess the hype around the movie generated by trailers, promos and advertisements. Using this data, along with other features a score is calculated for the movie and used to train a regression model. This model then predicts the opening weekend revenue for upcoming movies. This data can be used by the industry to devise their marketing and release strategy, thereby maximising revenue.
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