International Journal of Science and Research (IJSR)
Since Year 2012 | Open Access | Fully Refereed | Peer Reviewed

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Research Paper | Computer Science and Information Technology | India | Volume 10 Issue 11, November 2021

Revenue Predictor for Hollywood Movies using Sentiment Analysis and Regression

Moraish Kapoor | Karshni Mitra | Abhilash Arun

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.

Keywords: Language Processing, NLP, Machine Learning, ML, User interface, UI, Application Programming Interface, API

Edition: Volume 10 Issue 11, November 2021,

Pages: 108 - 114

Revenue Predictor for Hollywood Movies using Sentiment Analysis and Regression

How to Cite this Article?

Moraish Kapoor, Karshni Mitra, Abhilash Arun, "Revenue Predictor for Hollywood Movies using Sentiment Analysis and Regression", International Journal of Science and Research (IJSR), https://www.ijsr.net/get_abstract.php?paper_id=SR211030155631, Volume 10 Issue 11, November 2021, 108 - 114, #ijsrnet

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