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http://dx.doi.org/10.5351/KJAS.2016.29.4.657

Effect of online word-of-mouth variables as predictors of box office  

Jeon, Seonghyeon (Department of Statistics, Chonnam National University)
Son, Young Sook (Department of Statistics, Chonnam National University)
Publication Information
The Korean Journal of Applied Statistics / v.29, no.4, 2016 , pp. 657-678 More about this Journal
Abstract
This study deals with the effect of online word-of-mouth (OWOM) variables on the box office. From the result of statistical analysis on 276 films with audiences of more than five hundred thousand released in the Korea from 2012 to 2015, it can be seen that the variables showing the size of OWOM (such as the number of the portal movie rater, blog, and news after release) are associated more with the box office than the portal movie rating showing the direction of OWOM as well as variables showing the inherent properties of the film such as grade, nationality, release month, release season, directors, actors, and distributors.
Keywords
predictors of box office; online word-of-mouth (OWOM) variables; correlation coefficient; ANOVA test; chi square test; decision tree; canonical correlation analysis; factor scores plot; star plot;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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1 Sadikov, E., Parameswaran, A., and Venetis, P. (2009). Blogs as predictors of movie success. In Proceedings of the Third International ICWSM Conference, 304-307.
2 Yim, J. Y. and Hwang, B. Y. (2014). Data engineering: predicting movie success based on machine learning using twitter, KIPS Transactions on Software and Data Engineering, 3, 263-270.   DOI
3 Bae, J., Shim, B. J., and Kim, B.-D. (2010). Simultaneous effect between eWOM and revenues: Korea movie industry, Asia Marketing Journal, 12, 1-25.
4 Kim, Y. H. and Hong, J. H. (2013). A study for the drivers of movie box-office performance, The Korean Journal of Applied Statistics, 26, 441-450.   DOI
5 Kim, S. H. and Han, J. M. (2014). An analysis of motion picture box office performance: focusing on Korean movies released in 2012, Institute of Social Science, 53, 191-214.
6 Kim, S.-Y., Im, S., and Jung, Y. (2010). A comparison study of the determinants of performance of motion pictures: art film vs. commercial film, The Journal of the Korea Contents Association, 10, 381-393.
7 Kim, Y. H. and Hong, J. H. (2011). A study for the development of motion picture box-office prediction model, The Korean Journal of Applied Statistics, 18, 859-869.
8 Korean Film Council (2013). 2012 Korean film industry settlement, Korean Film, 35, 20-31.
9 Korean Film Council (2014). 2013 Korean film industry settlement, Korean Film, 47, 16-33.
10 Korean Film Council (2015). 2014 Korean film industry settlement, Korean Film, 59, 15-32.
11 Korean Film Council (2016). 2015 Korean film industry settlement, Korean Film, 71, 12-27.
12 Lee, I. H. and Cho, S. B. (2014). The analysis of the relationship between the box-office performance and the movie attributes using a quantile regression, Journal of the Korea Management Engineers Society, 19, 117-134.
13 Liu, Y. (2006). Word of mouth for movies: its dynamics and impact on box office revenue, Journal of Marketing, 70, 74-89.   DOI
14 Park, S.-H., Song, H.-J., and Jung, W.-K. (2011). The determinants of motion picture box office performance: evidence from Korean movies released in 2009-2010, Journal of Communication Science, 11, 231-258.