Forecasting the Rating of a New Movie Based on its Metadata

76

Abstract

The article describes an approach to predicting the rating of a new film based on data known prior to its release, using classic machine learning models.

General Information

Keywords: machine learning, film rating prediction

Journal rubric: Data Analysis

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2023130204

Received: 17.03.2023

Accepted:

For citation: Sologub G.B., Sazon N.S. Forecasting the Rating of a New Movie Based on its Metadata. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2023. Vol. 13, no. 2, pp. 77–84. DOI: 10.17759/mda.2023130204. (In Russ., аbstr. in Engl.)

References

  1. Baev M.A. Predicting movie ratings on IMDB. Materials of the 60th International Student Scientific Conference. Novosibirsk, 2022 - p. 281.
  2. Kirilina N.A., Gorbanyova E.N. Application of machine learning algorithms randomforest, gradientboosting, kneighbors for predicting box office revenues of movies. Software Engineering: Modern Trends in Development and Application (PI-2019) Kursk, March 11-12, 2019 - p. 25-28.
  3. IMDB Datasets [https://datasets.imdbws.com/].
  4. Google Colab [Electronic resource]. - Access mode: https://colab.research.google.com/ (accessed on September 01, 2022).

Information About the Authors

Gleb B. Sologub, PhD in Physics and Matematics, Associate Professor of the Department of Mathematical Cybernetics of Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0002-5657-4826, e-mail: glebsologub@ya.ru

Nikita S. Sazon, Master's Student at the Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University) (MAI), Moscow, Russia, ORCID: https://orcid.org/0000-0002-9816-4585, e-mail: nikitaS1598@gmail.com

Metrics

Views

Total: 180
Previous month: 22
Current month: 1

Downloads

Total: 76
Previous month: 4
Current month: 1