Abstract
This article describes a mathematical model designed to predict the box office of movies. The model is based on a neural network trained on data about films obtained from open sources. Computer experiments were performed by the method of “freezing”: with the help of a neural network calculations were performed with a gradual change in the value of one of the input parameters of the model, while the remaining input parameters were not changed. It is established that the size of the film budget has the greatest impact on the amount of box office among all other input parameters. However, its impact is not always positive. It is established that the United States, as a country that takes part in the production of the film, is able to have the greatest impact on box office compared to other countries. According to the research the duration of the film to varying degrees can affect the amount of box office. Moreover, the power of influence depends on such a factor as the genre of the film. As a rule, the power of this influence increases with the increasing semantic load of the film. The practical value of the study is that the created mathematical model can be used to optimize costs when planning the production of new films.
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