[4K2-IS-2e] Machine learning

[4K2-IS-2e-03] Predicting Anime Movie Box Office Revenue: An Approach Based on Original Manga and Production Information

〇Norio Nishioka¹, Kenji Tanaka¹ (1. The University of Tokyo)

キーワード：Anime, Box office predictions, Machine learning

With the growth of the anime movie market, predicting box office revenue has become increasingly important. Traditional movie revenue prediction research has mainly focused on factors such as news articles and reviews. However, there is a lack of research considering factors specific to anime movies. This study proposes an anime movie box office revenue prediction model that utilizes original manga sales related data, along with production information such as the director and original author, as features. Specifically, we construct models, using linear regression, multiple regression, and random forest, and compare their prediction accuracy. Using actual animated box office revenue data in Japan from 2012 and 2023, our evaluation suggests that the proposed model, particularly the simple linear regression model which uses the box office revenue by director, is effective in predicting the box office revenue of anime movies based on comics.