Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market
Joint Authors
Kim, Taegu
Hong, Jungsik
Kang, Pilsung
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-27
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM) effects in addition to screening-related information.
Nationality, genre, ratings, and distributors of motion pictures running concurrently with the target motion picture are used to describe the competition, whereas the numbers of informative, positive, and negative mentions posted on social network services (SNS) are used to gauge the atmosphere spread by WOM.
Among these candidate variables, only significant variables are selected by genetic algorithm (GA), based on which machine learning algorithms are trained to build forecasting models.
The forecasts are combined to improve forecasting performance.
Experimental results on the Korean film market show that the forecasting accuracy in early screening periods can be significantly improved by considering competition.
In addition, WOM has a stronger influence on total box office forecasting.
Considering both competition and WOM improves forecasting performance to a larger extent than when only one of them is considered.
American Psychological Association (APA)
Kim, Taegu& Hong, Jungsik& Kang, Pilsung. 2017. Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1140954
Modern Language Association (MLA)
Kim, Taegu…[et al.]. Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-16.
https://search.emarefa.net/detail/BIM-1140954
American Medical Association (AMA)
Kim, Taegu& Hong, Jungsik& Kang, Pilsung. Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1140954
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1140954