• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.57-72
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• 2018

Choi Dong-hoon's films tend to have not been well treated academically in Korea. But from the point of view that his works have succeeded in box office and survived in the market for some reason, there seems to be new possibilities to treat them. In this paper, the two movies with ten million audiences, and that are Choi's original scenario and caper film genre are tried to examine the success factors in box office on "making well made story". Often, well-made films have both genre-customary and creative aspects. Choi Dong-hoon's movies are the same. and faithfully follow the rules of caper film genre. At the same time, these two films have complex adaptive systematic creativity, in which multiple characters are self-organizing with their story patterns actively. And since there is a proper coexistence of customary and original aspects in the and , these two films are seemed to be at the edge of the chaos, which is the most market adaptable.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.615-622
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• 2014

The Korean film market has rapidly achieved an international scale, and this has led to a need for decision-making based on analytical methods that are more precise and appropriate. In this modern era, a highly advanced information environment can provide an overwhelming amount of data that is generated in real time, and this data must be properly handled and analyzed in order to extract useful information. In particular, the preprocessing of large data, which is the most time-consuming step, should be done in a reasonable amount of time. In this paper, we investigated a big data preprocessing method for predicting movie box office success. We analyzed the movie data characteristics for specialized preprocessing methods, and used the Hadoop MapReduce framework. The experimental results showed that the preprocessing methods using big data techniques are more effective than existing methods.

• Cartoon and Animation Studies
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• s.40
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• pp.287-314
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• 2015

This study tries to analyze the portfolio of production budget related to Hollywood animation movies released during the five years between 2010 and 2014, in order to investigate how blockbuster strategy made the box office performance. The analysis shows that this animation genre invested more than one thousand million dollars as the average budget for each film. It increased threefold in the box office result. In the production of Hollywood animation genre, 72.2% of its whole production money was found to use for movies investing more than one thousand million dollars. It is to show how the production of animation aimed for profit-making via blockbuster strategy recognized as the most successful portfolio strategy in the recent Hollywood film industry.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.527-538
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• 2014

The demand prediction is a critical issue for the film industry. As the social media, such as Twitter and Facebook, gains momentum of late, considerable efforts are being dedicated to prediction and analysis of hit movies based on unstructured text data. For prediction of trends found in commercially successful films, the correlations between the amount of data and hit movies may be analyzed by estimating the data variation by period while opinion mining that assigns sentiment polarity score to data may be employed. However, it is not possible to understand why the audience chooses a certain movie or which attribute of a movie is preferred by using such a quantitative approach. This has limited the efforts to identify factors driving a movie's commercial success. In this regard, this study aims to investigate a movie's attributes that reflect the interests of the audience. This would be done by extracting topic keywords that represent the contents of Twits through frequency measurement based on the collected Twitter data while analyzing responses displayed by the audience. The objective is to propose factors driving a movie's commercial success.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.167-173
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• 2017

With increased interest in the fourth industrial revolution represented by artificial intelligence, it has been very active to utilize bigdata and machine learning techniques in almost areas of society. Also, such activities have been realized by development of forecasting systems in various applications. Especially in the movie industry, there have been numerous attempts to predict whether they would be success or not. In the past, most of studies considered only the static factors in the process of prediction, but recently, several efforts are tried to utilize realtime social bigdata produced in SNS. In this paper, we propose the prediction technique utilizing various feedback information such as news articles, blogs and reviews as well as static factors of movies. Additionally, we also experimentally evaluate whether the proposed technique could precisely forecast their revenue targeting on the relatively successful movies.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.164-172
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• 2023

In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

• Korea Science and Art Forum
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• v.24
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• pp.1-13
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• 2016

The aim of this study is to find the reasons of success and failure of digital animations in terms of 'immersion.' For the purpose, the causes of immersion were analyzed through complex comparison about concepts and stories of two animation films with similar size of budget: 'Shrek 2' which ranked number 1 in the box-office of animation and 'Mars Needs Moms' which ranked number 172 in the same category. The complex results showed that immersion becomes bigger with creativity and popularity of the characters' outer concept, diversity and organic of the characters' inner concept, and diversity and consistency of the background. Moreover, gradual arrangement of characters' appearance in the story and increasing number of the characters, and visual changes around the plot heightening with a well-organized passage increase immersion. After all, immersion of digital animation requires developing creative, diverse, and popular concept and arranging and strengthening strategic well-organized plot of parts and the whole. This is the key to convergence it.

• Asia Marketing Journal
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• v.16 no.3
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• pp.77-100
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• 2014

Many researchers have analyzed the relationship between the financial success patterns of a motion picture and many other factors, such as the production cost, marketing, stars, awards, reviews, genre, and rating. Through these studies, many researchers and investors concluded that big budgets to make a blockbuster movie can serve as an insurance policy to meet their ROI; thus the box office is dominated by blockbuster movies. High-budget blockbuster movies are more likely to receive attention because these movies are more recognizable given their high expenses for production and casting. Therefore, audiences choose blockbusters in an effort to reduce the searching cost and to mitigate the possibility of a regrettable choice. This behavior of consumers, in turn, causes distributors to allocate screens for blockbusters, resulting in "concentration of blockbuster consumption." As such, low-budget films cannot easily become popular due to the lack of distribution. Indeed, low-budget films released on a small number of screens often end up becoming dismal failures. However, there are exceptional examples which are contrary to the general idea in the movie industry that a big budget and showings on a large number of screens can guarantee the success of a movie. Although researchers have attempted to analyze the performances of movies with small budgets, such movies are likely to be regarded as outliers and then be entirely discarded, as they are far from the 'three-sigma' range, especially given that previous research methodologies could not explain the financial success of such unique examples. This study attempts to explain the financial success at the box office of low-budget movies by applying the concept of the tunnel effect in quantum mechanics, as the phenomenon found in the movie industry is similar to a particle's movement in quantum physics. The tunneling effect is a phenomenon by which a particle without enough energy to pass over a potential barrier tunnels through it. Adopting the analogy, this study draws a tunneling probability function and cultural constant to forecast other outliers using the Schrödinger equation. Moreover, the study finds that word-of-mouth creates in the movie industry this phenomenon of finding outliers.

• Asia Marketing Journal
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• v.15 no.1
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• pp.43-55
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• 2013

Since movies are experience goods, consumers are easily influenced by other consumers' behavior. For moviegoers, box office rank is the most credible and easily accessible information. Many studies have found that the relationship between a movie's box office rank and its revenue departs from the Pareto distribution, and this phenomenon has been named "increasing returns to information." The primary objective of the current research is to apply the empirical model proposed by De Vany and Walls (1996) to the Korean movie market in order to examine whether the same phenomenon prevails in the Korean movie market. The other purpose of the present study is to provide managers with useful implications about the release timing of a movie by finding different curvatures that depend upon seasonality. The empirical test on the Korean movie market shows similar results as prior studies conducted on the U.S., Hong Kong, and U.K. movie markets. The phenomenon of increasing returns is generated by information transmission among consumers, which makes some movies become blockbusters and others bombs. The proposed model can also be interpreted in such a way that a change in the rank has a nonlinear effect on the movie's performance. If a movie climbs up the chart, it would be rewarded more than its proportion. On the other hand, if a movie falls down in the ranks, its performance would drop rapidly. The research result also indicates that the phenomenon of increasing returns occurs differently depending on when the movies are released. Since the tendency of the increasing returns to information is stronger during the peak seasons, movie marketers should decide upon the release timing of a movie based on its competitiveness. If a movie has substantial potential to incur positive word-of-mouth, it would be more reasonable to release the movie during the peak season to enjoy increasing returns. Otherwise, a movie should be released during the low season to minimize the risk of being dropped from the chart.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.351-364
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• 2021

Purpose: Fire load analysis was conducted to secure basic data for evaluating fire risk of educational facilities. In order to calculate the fire load through a preliminary survey, basic data related to the fire load of school facilities were collected. Method: The basic data were the definition and types of fire loads, combustion heat data for the calculation of fire loads. The fire load was evaluated by multiplying the combustion heat by the weight of the combustibles in the compartment when calculating the fire load. Result: As for the fixed combustible materials of A-elementary school, the floor was mainly made of wood, in consideration of emotion and safety in the classroom, music room, and school office, and the rest of the compartments were made of stone. The ceiling and walls were made of gypsum board and concrete, so they were not combustible. The typical inflammable items in each room were desks, chairs, and lockers in the classroom, and the laboratory equipment box and experimental tool box were the main components in the science room, and books, bookshelves, and reading equipment occupied a large proportion in the library room. Conclusion: 'The fire loads of A-elementary' schools according to the combustibles loaded were in the order of library, computer room, English learning room, teacher's office, general classroom, science hall, and music room.