Machine Learning Methods for Predicting the Popularity of Movies

Emmanuel Gbenga Dada

¹ Department of Mathematics and Statistics, Federal University Kashere, Gombe, Nigeria 

Email: [email protected] 

² Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria 

Email: [email protected]

^*Corresponding Author: Emmanuel Gbenga Dada, Email: [email protected]

The movie industry has grown into a several billion-dollar enterprise, and there is now a ton of information online about it. Numerous machine learning techniques have been created by academics and can produce effective classification models. In this study, different machine learning classification techniques are applied to our own movie dataset for multiclass classification. This paper's main objective is to compare the effectiveness of various machine learning techniques. This study examined five methods: Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), Bagging (BAG), Naive Bayes (NBS) and K-Nearest Neighbor (KNN), while noise was removed using All K-Edited Nearest Neighbors (AENN). These techniques all utilize previous IMDb dataset to predict a movie's net profit value. The algorithms predict the profit at the box office for each of these five techniques. Based on the dataset used in this paper, which consists of 5043 rows and 14 columns of movies, this study evaluates the performance of all seven machine learning techniques. Bagging outperformed other machine learning techniques with a 99.56% accuracy rate.

Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), Bagging (BAG), Naive Bayes (NBS), Movie popularity

David Opeoluwa Oyewola, Emmanuel Gbenga Dada (2022). Machine Learning Methods for Predicting the Popularity of Movies. Journal of Artificial Intelligence and Systems, 4, 65–82. https://doi.org/10.33969/AIS.2022040105.

[1] Latif, M.H., and Afzal, H. (2016). Prediction of movies popularity using machine learning techniques. IJCSNS Int J Comput Sci Netw Secur 16:127–131

[2] Masih, S., and Ihsan, I. (2019). Using academy awards to predict success of bollywood movies using machine learning algorithms. Int J Adv Comput Sci Appl 10:438–446

[3] Quader, N., Gani, M. O., and Chaki, D. (2017, December). Performance evaluation of seven machine learning classification techniques for movie box office success prediction. In 2017 3rd International Conference on Electrical Information and Communication Technology (EICT) (pp. 1-6). IEEE.

[4] Hafeez, E. (2012). Motion pictures as an agent of socialization: A comparative content analysis of demography of population on Indian Silver Screen and reported crime news in Pakistan (1976 to 2006). Business Review, 7(2), 23-50.

[5] Lee, K., Park, J., Kim, I., and Choi, Y. (2018). Predicting movie success with machine learning techniques: ways to improve accuracy. Inf Syst Front 20:577–588. https://doi.org/10.1007/s10796-016-9689-z

[6] Im, D., & Nguyen, M. T. (2011). Predicting box-office success of movies in the US Market. CS229, Stanford University, Fall.

[7] Simonoff, J. S., & Sparrow, I. R. (2000). Predicting movie grosses: Winners and losers, blockbusters and sleepers. Chance, 13(3), 15-24. https://doi.org/10.1080/09332480.2000.10542216

[8] Latif, M. H., & Afzal, H. (2016). Prediction of movies popularity using machine learning techniques. International Journal of Computer Science and Network Security (IJCSNS), 16(8), 127.

[9] Sharda, R., & Delen, D. (2006). Predicting box-office success of motion pictures with neural networks. Expert Systems with Applications, 30(2), 243-254. https://doi.org/10.1016/j.eswa.2005.07.018

[10] Cizmeci, B., & Ögüdücü, Ş. G. (2018, September). Predicting IMDb ratings of pre-release movies with factorization machines using social media. In 2018 3rd International Conference on Computer Science and Engineering (UBMK) (pp. 173-178). IEEE. https://doi.org/10.1109/ubmk.2018.8566661

[11] Tang, T. Y., Winoto, P., Guan, A., & Chen, G. (2018, February). “The Foreign Language Effect" and Movie Recommendation: A Comparative Study of Sentiment Analysis of Movie Reviews in Chinese and English. In Proceedings of the 2018 10th International Conference on Machine Learning and Computing (pp. 79-84). https://doi.org/10.1145/3195106.3195130 

[12] Wang, H., & Zhang, H. (2018, January). Movie genre preference prediction using machine learning for customer-based information. In 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 110-116). IEEE. https://doi.org/10.1109/CCWC.2018.8301647

[13] Gallaugher J (2008) Netflix case study: David becomes goliath. Gall com:1–16

[14] Jaiswal, S. R., and Sharma, D. (2017, November). Predicting success of bollywood movies using machine learning techniques. In Proceedings of the 10th Annual ACM India Compute Conference (pp. 121-124).

[15] Quader, N., Gani, M. O., Chaki, D., and Ali, M. H. (2017, December). A machine learning approach to predict movie box-office success. In 2017 20th International Conference of Computer and Information Technology (ICCIT) (pp. 1-7). IEEE.

[16] Lee, K., Park, J., Kim, I., and Choi, Y. (2018). Predicting movie success with machine learning techniques: Ways to improve accuracy. Information Systems Frontiers, 20(3), 577-588. https://dx.doi.org/10.1007/s10796-016-9689-z 

[17] Marović, M., Mihoković, M., Mikša, M., Pribil, S., and Tus, A. (2011, May). Automatic movie ratings prediction using machine learning. In 2011 Proceedings of the 34th International Convention MIPRO (pp. 1640-1645). IEEE.

[18] Jernbäcker, C., and Pojan, S. (2017). Predicting movie success using machine learning techniques. Master of Science, Computer Engineering Thesis, School of Computer Science and Communication, KTH.

[19] Bristi, W. R., Zaman, Z., and Sultana, N. (2019, July). Predicting IMDb Rating of Movies by Machine Learning Techniques. In 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-5). IEEE.

[20] Meenakshi, K., Maragatham, G., Agarwal, N., and Ghosh, I. (2018, April). A Data mining Technique for Analyzing and Predicting the success of Movie. In Journal of Physics: Conference Series (Vol. 1000, No. 1, p. 012100). IOP Publishing.

[21] Lee, J. H., Kim, Y. J., and Cheong, Y. G. (2020, August). Predicting Quality and Popularity of a Movie From Plot Summary and Character Description Using Contextualized Word Embeddings. In 2020 IEEE Conference on Games (CoG) (pp. 214-220). IEEE.

[22] Abidi, S. M. R., Xu, Y., Ni, J., Wang, X., and Zhang, W. (2020). Popularity prediction of movies: from statistical modeling to machine learning techniques. Multimedia Tools and Applications, 1-35.