Multi-genre Movie Data Analysis Using Pearson's Correlation
DOI:
https://doi.org/10.32628/CSEIT1952102Keywords:
Movies, Success, Attributes, Pearson’s Correlation.Abstract
The success of a movie plays an important role because it usually involves huge amounts of investments. Thus it becomes important to know beforehand whether the movie will be successful or not. The aim of our work is to prove that various attributes or factors related to a movie could prove useful in predicting the success or failure of a movie. Since one single attribute is not sufficient to predict the success of a movie, we’ve used multiple attributes and the comparisons between various attributes and their correlation for the success prediction. Therefore, in this paper we are considering a statistical technique called Pearson’s correlation coefficient in finding out which factors are highly correlated with a movie’s ratings.
References
- Javaria Ahmad, Prakash Duraisamy, Amr Yousef, Bill Buckles, "Movie Success Prediction Using Data Mining".
- Jiawei Han, Jian Pei, and Micheline Kamber. "Data Mining Concepts and Techniques", 2012.
- M. Saraee, S. White, and J. Eccleston. "A data mining approach to analysis and prediction of movie ratings", 2004.
- Nithin VR, Pranav My, Sarath Babu PBz, Lijiya Az, "Predicting Movie Success Based on IMDb Data",2017.
- K Meenakshi1, G Maragatham2, Neha Agarwal3 and Ishitha Ghosh4, "A Data mining Technique for Analyzing and Predicting the success of Movie", 2018.
- "Success Prediction of Films at Box Office Using Machine Learning" by Parag Ahivale, Omkar Acharya.
- "Predicting box-office success of motion pictures with neural networks" by Ramesh Sharda, Dursun Delen, 2015.
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