An inside look into the complexity of box-office revenue prediction in China

Jia Xiao, Xin Li, Shanzhi Chen, Xuhui Zhao and Meng Xu

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 1, 1550147716684842

Abstract: 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.

Keywords: Revenue; big data; linear regression; Internet of things; video website; correlation coefficient (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:1:p:1550147716684842

DOI: 10.1177/1550147716684842

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