Using movie posters for prediction of box-office revenue with deep learning approach

Özkan, Kemal; Atak, Osman Nuri; Işık, Şahin

doi:10.1109/siu.2018.8404649

Cited by 3 publications

(1 citation statement)

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“…The features that can influence the movie box office have also been explored in past research. The relationship between the movie poster and the box office was explored using the Inception-V3 model and reached an accuracy of 33% [7]. In addition to movie posters, the audiences` reaction was also tested by emotion recognition which can classify up to seven different emotions, researchers successfully predicted movie ratings [8].…”

Section: Research On Movie Box Office Predictionmentioning

confidence: 99%

A Deep Learning Approach to Predict Film Box Office in the Chinese Domestic Market Based on Feed-Forward Neural Network

Lan¹,

He²

2023

Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Han

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With the booming development of the Chinese film market, China has become the world's second-largest film market and the main engine for industry development. In order to improve the efficiency and predictive power of movie box office prediction in the Chinese domestic market, this study proposes a Feed-Forward Neural Networks model with two and three hidden layers by predicting the box office of 478 films in the Chinese market from 2019 to 2022 using movie metadata, post-release rating data, social media related big data and theaters arrangement. Loss curves for the training and validation sets are presented for model comparison with 400 films being used as the training set and 78 films being used as the validation set. The results show that the Feed-Forward Neural Network with three hidden layers has greater fitting and predictive power in model generation, enabling it to effectively predict the movie box office.

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Section: Research On Movie Box Office Predictionmentioning

confidence: 99%