• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.221-229
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• 2020

This study aims to find out predictors of a movie's eventual box office, focusing on a movie's box office rank on an opening day. For an empirical analysis, I use data of 794 commercial movies released in the Korean theatrical exhibition market during the recent five years(2013~2017). The regression analysis shows that being box office number one on an opening day has statistically significant impact on a movie's final box office. A movie's quality, measured by audience's review, does not give significant impact on top1 movie's final success. Indexes such as increase of showing number on Sunday are strongly related to a movie's economic success. The additional analysis on box office number one movie on an opening day, totally 158 movies, finds that box office growth rate on a second week is strongly related to a movie's final success. Lastly, correlation coefficient of a movie's opening day box office and final box office does not show consistent growth when the coefficient is compared yearly. This study might have meaning in that it proposes new box office predictors and shows the relation of the indexes and a movie's final performance empirically.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.108-115
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• 2013

This study focused on whether the existence and type of originals have any effects on box-office performance of the movie. Cultural products have characteristics of experience goods of which consumers hardly know the value of the products before they actually experience the products. To reduce the uncertainty, movie producers may want to use existing contents already made for other type of cultural products, which is generally called of One Source Multi Use. Using 381 Korean box-office data during January 2010 and September 2012, this study found that, first, the existence of original affects positively the movie's box office performance, second, the fiction based original has a positive effect on the movie's box office performance while cartoon and movie/TV based originals do not, and third, the movie type(commercial movie) positively moderates the relationship between fiction based original and movie performance. This study showed that box-office performance is not only affected by the characteristics of the movie itself, but also affected by other conditions including the use of existing originals created for other purposes.

• Knowledge Management Research
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• v.16 no.2
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• pp.213-226
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• 2015

This study investigates the effects of the volume and valence of the movie reviews on the weekly box-office revenues. Existing literature shows that only the volume of movie reviews influences the box office results, but not valence. However, it has limitations in that it includes only the positivity or negativity ratio of the reviews, not the strength of the valence. In order to overcome such limitations, this study includes the degree of valence. This study used approximately 1.3 million reviews about 300 movies as the sample which was collected from a movie review site in an online portal, that is, movie.naver.com. SPSS was used to test the proposed model. The results of this study show different findings compared to those of the previous studies. First, the volume of movie reviews has been a consistent predictor of the box office success throughout the study periods. Second, the ratio of positive reviews has no impact on the first week's results, but shows significant effects on the box office results during the second week. Third, regarding the degree of positivity or negativity in reviews, the degree of positivity has a significant impact on the box office results only during the first week, while the degree of negativity does not have any significant effects on the results. However, from the second week, the situation is reversed; that is, only the degree of negativity has a significant impact on the box office results, but not the positivity.

• Design Convergence Study
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• v.14 no.4
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• pp.1-16
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• 2015

This study aims to understand distribution of the sentimental words on each genre and find relationship between box office performance and sentimental words in movie review using 673 movies that have more than 1,000 reviews. For the analysis, crawling movie reviews and made data was composed movie genre, movie name, sales, attendance, screen, normal attendance, 7 sentimental words. For analysis results, we used correlation analysis and Parallel coordinates. As a results, First, the highest box office value of the genre is comedy and the lowest box office value of the genre is horror through analyze box office on each genre. Secondly, Movie genre of fantasy feel a lot of boring emotion and Movie genre of SF feel a lot of anger emotion even if 'Happy' and 'Surprise' have highest sentiment value on every genre. Third, We found 'Anger' increase sentimental value when 'Disgust' increase sentimental value and 'Surprise' decrease sentimental value when 'Happy' increase sentimental value through analyze correlation relationship between sentimental words using total data. Fourth, We found 'Happy' have linear relationship between box office and 'Fear' have non-linear relationship between box office through analyze sentimental words according to box office performance.

• ETRI Journal
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• v.36 no.4
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• pp.581-590
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• 2014

This study investigates the impact of tweets on box office revenue. Specifically, the study focuses on the times when tweets were written by examining the impact of pre- and post-consumption tweets on box office revenue; an examination that is based on Expectation Confirmation Theory. The study also investigates the impact of intention tweets versus subjective tweets and the impact of negative tweets on box office revenue. Targeting 120 movies released in the US between February and August 2012, this study collected tweet information on a daily basis from two weeks before the opening until the closing and box office revenue information. The results indicate that the disconfirmation that occurs in relation to the total number of pre-consumption tweets for a movie has a negative impact on box office revenue. This premise suggests that the formation of higher expectations of a movie does not always result in positive results in situations where tweets on perceived movie quality after watching spread rapidly. This study also reveals that intention tweets have stronger effects on box office revenue than subjective tweets.

• Knowledge Management Research
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• v.18 no.2
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• pp.65-83
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• 2017

Word-of-mouth (WOM), the communication between consumers offline, has transformed to include electronic word-of-mouth(eWOM), which has grown in its influence due to the advancements in communication technology. Despite the fact that many researchers have studied the impact of WOM and eWOM on the performance of movies in the movie industry, there still exists much controversy. Therefore, this study investigates the relationship of eWOM's volume and valence with the box office revenue for 2 years in Korean movies industry. The results show that the volume of eWOM, which is expected to related to awareness diffusion, is more important than the valence in the early stage of movie release. And in the later stage, the valence of eWOM which is expected to related to persuasion effect influences the box office revenue. In addition, the relationship of the volume and valence on box office revenue in both early and later stage can be increased through the interaction with the star power which raises the familiarity or the movie genre which causes the high arousal.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.9
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• pp.437-444
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• 2017

Although many studies tried to predict movie revenues in the last decade, the main focus is still to learn an efficient forecast model to fit the box-office revenues. However, the previous works lack the analysis about why the prediction errors occur, and no method is proposed to reduce the errors. In this paper, we consider the prediction error comes from the competition between the movies that are released in the same period. Our purpose is to analyze the competition value for a movie and to predict how much it will be affected by other competitors so as to improve the performance of movie box-office prediction. In order to predict the competition value, firstly, we classify its sign (positive/negative) and compute the probability of positive sign and the probability of negative sign. Secondly, we forecast the competition value by regression under the condition that its sign is positive and negative respectively. And finally, we calculate the expectation of competition value based on the probabilities and values. With the predicted competition, we can adjust the primal predicted box-office. Our experimental results show that predictive competition can help improve the performance of the forecast.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.859-869
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• 2011

Interest has increased in academic research regarding key factors that drive box-office success as well as the ability to predict the box-office success of a movie from a commercial perspective. This study analyzed the relationship between key success factors of a movie and box office records based on movies released in 2010 in Korea. At the pre-production investment decision-making stage, the movie genre, motion picture rating, director power, and actor power were statistically significant. At the stage of distribution decision-making process after movie production, among other factors, the influence of star actors, number of screens, power of distributors, and social media turned out to be statistically significant. We verified movie success factors through the application of a Multinomial Logit Model that used the concept of choice probabilities. The Multinomial Logit Model resulted in a higher level of accuracy in predicting box-office success compared to the Artificial Neural Network and Discriminant Analysis.

• Journal of the Korea Safety Management & Science
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• v.19 no.4
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• pp.169-182
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• 2017

Predicting a box office gross in the film industry is an important goal. Many works have analyzed the elements of a film making. Previous studies have suggested several methods for predicting box office such as a model for distinguishing people's reactions by using a sentiment analysis, a study on the period of influence of word-of-mouth effect through SNS. These works discover that a word of mouth (WOM) effect through SNS influences customers' choice of movies. Therefore, this study analyzes correlations between a box office gross and a ratio of people reaction to a certain movie by extracting their feedback on the film from before and after of the film opening. In this work, people's reactions to the movie are categorized into positive, neutral, and negative opinions by employing sentiment analysis. In order to proceed the research analyses in this work, North American tweets are collected between March 2011 and August 2012. There is no correlation for each analysis that has been conducted in this work, hereby rate of tweets before and after opening of movies does not have relationship between a box office gross.

• Asia Marketing Journal
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• v.21 no.1
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• pp.1-21
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• 2019

Online platforms often provide rating information to customers to relieve the uncertainty they encounter when purchasing experience goods. Prior research has focused mostly on the roles of rating volume and the valence of an average rating among the various possibilities. However, less frequently investigated is the effect of rating dispersion, which may be associated with uncertainty regarding how well a product fits a customer's personal preference, on new trials of experience goods. In this study, we examine the effect of rating dispersion on new trials of experience goods and identify the conditions which intensify or reduce the effect. Empirical analyses of movie box office sales data and online rating data reveal three interesting findings. First, movie sales decrease as movie ratings become increasingly dispersed. Second, the negative effect of rating dispersion on movie sales is more pronounced with more rating volume. Third, this negative effect weakens when additional information about a movie is available (i.e., higher average rating, greater star power, and time since its release). We discuss the academic and practical implications of our findings.