USING MACHINE LEARNING TO PREDICT OSCAR WINNERS
DOI:
https://doi.org/10.24867/30BE07MilijevicKeywords:
Machine Learning, Logistic Regression, SVM, XGBoostAbstract
The study focused on predicting the winners of the Oscar award for Best Picture and for acting achievements. This research is motivated by its significance to the film industry. The algorithms used include: Logistic Regression, SVM, Random Forest, Bagging, XGBoost, and Neural Networks. Model evaluation was conducted using 10-fold cross- validation. In the first prediction, Random Forest demonstrated the best performance with an accuracy of 91.59%, while in the second prediction, XGBoost achieved an accuracy of 84.39%.
References
[1] Jeffrey S. Simonoff, Ilana R. Sparrow, Predicting movie grosses: Winners and losers, blockbusters and sleepers, 2000.
[2] Iain Pardoe, "Just how predictable are the Oscars?", 2005.
[3] Iain Pardoe, Dean K. Simonton, Applying discrete choice models to predict Academy Award winners, 2008.
[4] Predicting the 85th Academy Awards: Stephen Barber, Kasey Le, Sean O’Donnell December 13, 2012
[5] Prediction of Movies popularity Using Machine Learning Techniques: Muhammad Hassan Latif, Hammad Afzal, National University of Sceinces and technology, Pakistan, August 2016.
[6] Performance evaluation of seven machine learning classification techniques for movie box office success prediction: Nahid Quader, Md. Osman Gani, Dipankar Chaki , December 2017.
[7] Predicting the “Best Picture” Oscar Award Winner: Paul Ables, 2018.
[8] Revisiting predictions of movie economic success: random Forest applied to profits: Thaís Luiza Donega e Souza, & Marislei Nishijima, Ricardo Pires, Mart 2023.
[9] https://www.kaggle.com/datasets/matevaradi/oscar-prediction-dataset(pristupljeno u januaru 2024.)
[10] https://zenodo.org/records/4244691(pristupljeno u januaru 2024.)
[2] Iain Pardoe, "Just how predictable are the Oscars?", 2005.
[3] Iain Pardoe, Dean K. Simonton, Applying discrete choice models to predict Academy Award winners, 2008.
[4] Predicting the 85th Academy Awards: Stephen Barber, Kasey Le, Sean O’Donnell December 13, 2012
[5] Prediction of Movies popularity Using Machine Learning Techniques: Muhammad Hassan Latif, Hammad Afzal, National University of Sceinces and technology, Pakistan, August 2016.
[6] Performance evaluation of seven machine learning classification techniques for movie box office success prediction: Nahid Quader, Md. Osman Gani, Dipankar Chaki , December 2017.
[7] Predicting the “Best Picture” Oscar Award Winner: Paul Ables, 2018.
[8] Revisiting predictions of movie economic success: random Forest applied to profits: Thaís Luiza Donega e Souza, & Marislei Nishijima, Ricardo Pires, Mart 2023.
[9] https://www.kaggle.com/datasets/matevaradi/oscar-prediction-dataset(pristupljeno u januaru 2024.)
[10] https://zenodo.org/records/4244691(pristupljeno u januaru 2024.)
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Published
2025-03-04
Issue
Section
Electrotechnical and Computer Engineering
