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Early Predictions of Movie Success: The Who, What, and When of Profitability
Journal article   Peer reviewed

Early Predictions of Movie Success: The Who, What, and When of Profitability

Michael T Lash and Kang Zhao
Journal of management information systems, Vol.33(3), pp.874-903
07/02/2016
DOI: 10.1080/07421222.2016.1243969
url
https://arxiv.org/pdf/1506.05382View
Open Access

Abstract

We focus on predicting the profitability of a movie to support movie-investment decisions at early stages of film production. By leveraging data from various sources, and using social network analysis and text mining techniques, the proposed system extracts several types of features, including "who" is in the cast, "what" a movie is about, "when" a movie will be released, as well as "hybrid" features. Experiment results showed that the system outperforms benchmark methods by a large margin. Novel features we proposed made weighty contributions to the prediction. In addition to designing a decision support system with practical utility, we also analyzed key factors of movie profitability. Furthermore, we demonstrated the prescriptive value of our system by illustrating how it can be used to recommend a set of profit-maximizing cast members. This research highlights the power of predictive and prescriptive data analytics in information systems to aid business decisions.
prescriptive analytics predictive analytics social network analysis text mining decision support movie profitability movie investments

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