In the theater-based movie industry, it is known that the diversity of movie consumption is hindered due to concentrated consumption. This study extends the existing discussions on the concentration of movie consumption in theaters to the concentration of online movie consumption. In addition, the study analyzes the impact of Covid-19 pandemic on movie consumption and the concentration thereof. For analysis, panel data for the period from 2012 through 2021 were collected by utilizing the box office data of the Korean Film Council. As a result of the analysis, it was found that the concentration of consumption by movie, country, and genre was higher in theaters than online. Further, the concentration of movie consumption has increased both in theaters and online until the outbreak of Covid-19 pandemic. During the Covid-19 pandemic period, the size of consumption has decreased both in theaters and online, while the concentration of consumption by movie online has increased. The result of this study implies a need for policy-level efforts to convert the trend of consumption concentration for long-term development of the movie industry with secured diversity of movie consumption, and for this, the study suggests that the use of online media would be useful.
Journal of Korea Entertainment Industry Association
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v.13
no.7
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pp.1-13
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2019
This study tried to explore the contents of film critics' reviews reported in the press. Based on fifty nine Korean movies with over 100,000 audience in 2017, this study collected 1113 reviews from fifty five movies with the exception of four without reviews. This study focused on the correlation between film's overall quality and four evaluation items such as directing, acting, story, and the visual. Examining the difference in the report timing of the review, the length of the review, and the intensity of the opinion, this study also analyzed the relationship between the internal aspects of reviews and box office performance. According to the results, the valence of critics' reviews was generally positive. Looking at the difference of reporting time, this valence was higher in the week before release than in the release week of film. The evaluation items of reviews were highly covered both before movie release and in the opening week. These were significantly declined in the second week of release. In the relationship between the number of reviews by each movie and box office performance, a positive correlation was found.
The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.
Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.
The goal of this study is analysing a box office success of The Handmaiden in terms of modified space-time and character. The movie which has original novel induces desire of watching by decreasing property of experience good of movie based narrative of novel. Contrary to novel that is set in Victorian age, the movie changed contents that make a character who realizes masculine of colonialism and women oppressed by man escape through transcending class by adopting period of Japanese occupation. It hereby decreases negative effect by substituting growth and solidarity of women for the element of homosexuality. Also the gender discussion about crimes against female when the movie was running increases factor of sympathy of characters and accord with subject of the movie. Beside that, The reasons of success are detector, star system of actor, effective public marketing of movie trailer and selection of movie won the award for best picture at a film festival.. Movie through adapting novel enhances ability of various creation and blow up appreciation of spectator. The differentiation of adapted hit movie is that the altered content is creative, has subject that corresponding with universal awareness transcending space-time and expresses property of media effectively.
Recently, crowdfunding platforms have received attention as one of the content investment platforms for the public. This research attempts to explore the influencing factors on the success of movie euqity crowdfunding project. We use 'number of texts', 'number of images', 'star influence power', 'IP-based movie project', 'movie production stage', 'box office prediction', 'investment capital ratio', 'amount of surplus available investment', 'profit calculation method' and 'minimum investment amount' as independent variables. And we examined how these factors affects the achievement rate of movie crowdfunding. As a result of multiple regression analysis, 'movie production stage', 'investment capital ratio', 'amount of surplus available investment' and 'profit calculation method' have a significant effect on the crowdfunding achievement rate. In addition, the results of this research can be used for reference when planning film crowdfunding projects.
When studying the film industry, researchers have seldom addressed the dynamic interaction between marketing information and word of mouth in the motion picture industry mainly because of the limitation of traditional research methodologies. This study explores integration and competition among important variables influencing on audience's choice on movie selection, particularly by using a new method of agent-based modeling including competitive environment. Decision process of moviegoer composed of transition probability based on multinomial logit model, considering marketing and box-office information, critique, and word of mouth from other moviegoers. After validating the fitness of market share among released movies, this study conducted a set of simulation experiments considering several variables such as market size, change of weight between variables, and movie performance under competition. Propositions are derived from the simulation results is also suggested for future research.
Journal of Korea Society of Digital Industry and Information Management
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v.14
no.4
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pp.149-154
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2018
A game story that used to be free needs a work of concrete and artificial organizing and arranging these days. This is because a game story is frequently made into a new genre such as a movie or an animation. As shown in many previous studies, most of the movies made from successful digital games failed to receive satisfying box office results. To overcome this, narratively completed storytelling should be presented from the development phase of a game. The methods are as follows: It is necessary to maximize the synergy effect through the interaction between storytelling experts, game developers, animators, and movie producers in developing a game. This will help to create a game with more sophisticated and complete narrative structure than now. It is necessary to secure the diversification of game genres. Currently in Korea, online games are unusually leading the game industry. PC games or console games are more advantageous than online games for putting a finished narrative structure into a game.
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.
This article attenpts to analyze, from the perspective of post-colonialism, 'Goemul'(English title, The Host), the Korean blockbuster movie that scored the greatest box-office success in the history of the Korean cinema. As Goemul eagerly copies the monster movie, a representative genre of Hollywood movies, it has close affinity with Hollywood blockbuster movie in many repects. At the same time, however, it also contains a resistance discourse that criticizes and mocks colonial of Korean society under American influences. This movie successfully carries out a post-colonial cultural translation that transforms mimicry into resistance to colonialsim. Hence, this artcle focuses on how Goemul borrows many aspects of the Hollywood monster movie but goes beyond the simple copying of it to reach post-colonial signification subverting the existing cultural regime.
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