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Forecasting Movies Box Office Revenue

Student: Nadezda Kirilina

Supervisor: Ilya Schurov

Faculty: Faculty of Communications, Media, and Design

Educational Programme: Data Journalism (Master)

Year of Graduation: 2018

The paper discusses the main indicators and terms used in the forecasting of socio-economic phenomena and processes, provides an overview of the main works, the purpose of which is to predict indicators related to movies and film production, describes the methods of machine learning, which will be used in the practical part of the work. The market of the world film industry, its features and tendencies were characterized, classes of films with high profitability are allocated, the reasons of a cultural distance between the markets of hire are investigated. The study built models advanced forecasting box-office receipts and user rating. Model prediction accuracy is compared, factors that have the greatest impact on cash collections and user ratings of movies are determined. At the end of the work there is a list of used sources and literature, the application in which the program codes in Python are located.

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