Abstract
As the size of investment for movie production grows bigger, the need for predicting a movie’s success in early stages has increased. To address this need, various approaches have been proposed, mostly relying on movie reviews, trailer movie clips, and SNS postings. However, all of these are available only after a movie is produced and released. To enable a more earlier prediction of a movie’s performance, we propose a deep-learning based approach to predict the success of a movie using only its plot summary text. This paper reports the results evaluating the efficacy of the proposed method and concludes with discussions and future work.- Anthology ID:
- W19-3414
- Volume:
- Proceedings of the Second Workshop on Storytelling
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Francis Ferraro, Ting-Hao ‘Kenneth’ Huang, Stephanie M. Lukin, Margaret Mitchell
- Venue:
- Story-NLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 127–135
- Language:
- URL:
- https://aclanthology.org/W19-3414
- DOI:
- 10.18653/v1/W19-3414
- Cite (ACL):
- You Jin Kim, Yun Gyung Cheong, and Jung Hoon Lee. 2019. Prediction of a Movie’s Success From Plot Summaries Using Deep Learning Models. In Proceedings of the Second Workshop on Storytelling, pages 127–135, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Prediction of a Movie’s Success From Plot Summaries Using Deep Learning Models (Kim et al., Story-NLP 2019)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/W19-3414.pdf
- Data
- CMU Movie Summary Corpus