Social Network Analysis of the Professional Community Interaction - Movie Industry Case

P. 36–50.

Karpov I., Roman Marakulin

With the rise of the competition in the movie production market, because of new players such as Netflix, Hulu, HBO Max, and Amazon Prime, whose primary goal is producing a large amount of exclusive content in order to gain a  competitive advantage, it is extremely important to minimize the number of unsuccessful titles. This paper focuses on new approaches to predict film success, based on the movie industry community structure, and highlights the role of the casting director in movie success. Based on publicly available data we create an ``actor''-``casting director''-``talent agent'' - ``director'' communication graph and show that usage of additional knowledge leads to better movie rating prediction.

Keywords: machine learning, social network analysis, Prediction, Graph Embeddings, Movie Rating, IMDb

Publication based on the results of: Applied Network Analysis for the Solution of Current Problems of the State, Business and Society: Methodological Developments and Practical Implementations (2022)

In book

Data Analytics and Management in Data Intensive Domains. 23rd International Conference, DAMDID/RCDL 2021, Moscow, Russia, October 26–29, 2021, Revised Selected Papers

Springer, 2022.