Film Box Office Forecasting Methods Based on Partial Least Squares Regression Model-Reference-Cited by-同舟云学术

Film Box Office Forecasting Methods Based on Partial Least Squares Regression Model

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 11th International Conference on Computer Modeling and Simulation - ICCMS 2019
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Author:

Zhu Huike¹,Tang Zhongjun¹

Affiliation:

1. Research Base of Beijing Modern Manufacturing Development, College of Economics and Administration, Beijing University of Technology, chaoyang district, Beijing

Publisher

ACM Press

Reference22 articles.

1. Baek, H., Oh, S., & Yang, H. D. 2017. Electronic word-of-mouth, box office revenue and social media. Electron. Commer. R. A. 22, 3 (Mar-Apr. 2017), 13--23.

2. Bhave, A., Kulkarni, H., & Biramane, V. 2015. Role of different factors in predicting movie success. International Conference on Pervasive Computing (Pune, India, January 08--10, 2015). IEEE, 1--4.

3. Biramane, V., Kulkarni, H., & Bhave, A. 2016. Relationships between classical factors, social factors and box office collections. International Conference on Internet of Things and Applications (Pune, India, January 22--24, 2016). IEEE, 35--39.

4. Boatwright, P., Basuroy, S., & Kamakura, W. 2007. Reviewing the reviewers: The impact of individual film critics on box office performance. Quant. Market. Econ. 5, 4 (Aug. 2007), 401--425.

5. Devedi, P., Sujatha, R., & Pathak, R. 2017. A study on parameters of online reviews content that influence consumers buying behaviour- an Indian perspective. J. Bus. Ret. Manag. Res. 11, 4 (Aug. 2017), 1--13.

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