An inside look into the complexity of box-office revenue prediction in China
Author(s) -
Jia Xiao,
Xin Li,
Shanzhi Chen,
Xuhui Zhao,
Meng Xu
Publication year - 2017
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1177/1550147716684842
Subject(s) - computer science , mainstream , revenue , china , big data , box office , barometer , the internet , regression analysis , data science , data mining , advertising , machine learning , world wide web , business , philosophy , physics , theology , accounting , quantum mechanics , political science , law
In this article, we discuss various elements contributing to exerting influence on box office in China, which are divided into internal and external factors. Since these factors could merely be quantified by online data sources partially or inaccurately, we propose that relativity analysis is more reasonable than precise revenue prediction. Trailer is selected as the combination of movie content and online behavior prior to releasing. Indexes from seven mainstream video websites are retrieved by the designed big data system which is integrated with the Internet of things technology. Correlation coefficients of different time periods are calculated. We apply multiple linear regression with stepwise method in modeling and prove that watching counts of 1 week before releasing on Youku is the barometer of market performance, especially the first week revenues. We also manifest the power of influential users through constructing Sina Weibo acquisition and analysis system.
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