• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.419-428
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• 2015

Stone is a hybrid genre movie in which two different film genres coexist; one is a gangster movie, the other Baduk movie. This film deals with a relationship between an old gangster boss and a young Baduk player. The coexistence of two different worlds becomes a reason for a unique ambiance of this film, because Stone is dynamic and brutal as much as static and meditative. Firstly, this article aims to analyze the narrative structure and characters of this film comparing with conventions of gangster movie genre, especially 'jopok film' of Korean cinema. Secondly, we examine characters of this film and their relationship. Since the economic crisis under the IMF structure, a great part of korean gangster movie has represented the weakness of the fatherhood and the disorganization of family. However, in Stone, the friendship between two heroes, Namhae and Minsu, turns to a father-son relationship. In this way, Stone transformed conventions of film genre.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.153-168
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• 2017

Existing researches on movie genre have been focusing on the relationship between a specific genre and performance of a movie. However, most of films cross into multiple genres and new approach is needed for analyzing a genre network. In this study social network analysis was used to analyze the genre centrality and its relationship with movie performance by developing a genre network, i.e. network among multiple genres constructed via genre co-occurrence pattern in a specific movie. Three index of genre centrality, eigenvector centrality, degree centrality, and bonacich power centrality, were tested for the valued genre network. Results showed that the relationship between genre centrality and movie performance appeared to be inverted U-shaped. This empirical finding is in line with the theory of ambidexterity which emphasizes the balance of exploration and exploitation. In addition, this study can provide practical implications for movie producers, distributors, and theaters that need to develop genre strategies.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.43-48
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• 2017

Movie ratings are crucial for recommendation engines that track the behavior of all users and utilize the information to suggest items the users might like. It is intuitively appealing that information about the viewing preferences in terms of movie genres is sufficient for predicting a genre of an unlabeled movie. In order to predict movie genres, we treat ratings as a feature vector, apply a Bernoulli event model to estimate the likelihood of a movie being assigned a certain genre, and evaluate the posterior probability of the genre of a given movie by using the Bayes rule. The goal of the proposed technique is to efficiently use movie ratings for the task of predicting movie genres. In our approach, we attempted to answer the question: "Given the set of users who watched a movie, is it possible to predict the genre of a movie on the basis of its ratings?" The simulation results with MovieLens 1M data demonstrated the efficiency and accuracy of the proposed technique, achieving an 83.8% prediction rate for exact prediction and 84.8% when including correlated genres.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.265-283
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• 2022

MovieLens data consists of recorded movie evaluations that was often used to measure the evaluation score in the recommendation system research field. In this paper, we provide additional information obtained by clustering user-specific genre preference information through movie evaluation data and movie genre data. Because the number of movie ratings per user is very low compared to the total number of movies, the missing rate in this data is very high. For this reason, there are limitations in applying the existing clustering methods. In this paper, we propose a convex clustering-based method using the pairwise fused penalty motivated by the analysis of MovieLens data. In particular, the proposed clustering method execute missing imputation, and at the same time uses movie evaluation and genre weights for each movie to cluster genre preference information possessed by each individual. We compute the proposed optimization using alternating direction method of multipliers algorithm. It is shown that the proposed clustering method is less sensitive to noise and outliers than the existing method through simulation and MovieLens data application.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.51-59
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• 2010

There have been proposed several movie recommendation algorithms based on Collaborative Filtering(CF). CF decides neighbors whose ratings are the most similar to each other and it predicts how well users will like new movies, based on ratings from neighbors. This paper proposes a new method to improve the result predicted by CF based on genres of the movies seen by users. The proposed method can be combined to the most of all existing CF algorithms. In this paper, a performance evaluation has been conducted between an existing simple CF algorithm and CF-Genre that is the proposed genre-based method added to the CF algorithm. The result shows that CF-Genre improves 3.3% in prediction performance over existing CF algorithms.

• 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.

• Journal of Fashion Business
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• v.9 no.6
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• pp.141-159
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• 2005

Targeting a film that is the medium of having powerful influence upon the masses, the present study examined about a role and characteristics in the movie costume, and a role of costume designers, which are shown in process of being changed the film costume. There are many designers who were in charge of the film costume, but the present study examined centering on designers who participated aiming to create the image of a character from the stage of manufacturing a movie. It presented and analyzed visual materials by dividing four genres such as a historical drama movie, a horror movie, a fantasy movie, and a modern-play movie, and by selecting a typical work. A Historical drama movie needs to be investigated costume by the historical background in a movie, but inside it was shown clothes that were elaborately reproduced and newly created. A horror movie plays a role of medium that reflects the human society and the internal mentality of a human being along with the attribute of entertainment. As a genre that requires much costume, make-up and special effect aiming at dramatic effect, a role of film costume possesses great weight. As a fantasy movie is a field based on 'fiction' of a writer who creates a work, it is a field that requires creativity of a costume designer most. As a modern-play movie is what reproduces reality, it best reflects the phases of that time, and is the field that is influenced by costume or fashion trend. Costume needs to be designed in a bid to allow spectators to be inspired the wholly united and harmonious mood with leading a story of a movie, and the individual image.

• Korean journal of communication and information
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• v.51
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• pp.47-64
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• 2010

Korea film market is heterogeneously divided market that comes from competition between Korean movies and foreign imported movies. This research empirically analyzes genre differentiation in Korean film market with three dimensions (film audience preference, production and import, box office hit). The results indicate that, first, audiences who preferring Korean movie preferred 'cultural factor oriented genres', but audiences who preferring foreign movie preferred 'high budget oriented genres'. Second, imported foreign movie genre distribution was little bit different with box office hit genre of foreign movies. Foreign movie was imported not only hit genre (action genre) but also low cost genre (comedy and Drama/melodrama genre), but most of all Korean film was produced in box office hit genres (comedy and Drama/melodrama genre), third, Korean movies hit a box office in comedy and Drama/melodrama genre, but foreign movies hit a box office in action and SF/Fantasy genre. Those results show that Korea movies' genres are concentrated very much in cultural factor oriented genre. Those results can give implication of diversity policy and movie production strategy of Korea film market.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.13-19
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• 2021

While watching the movie, the audience shows various emotional reactions. Emotional reactions such as sadness and anger, joy and anger appear depending on the storyline of the film. This aspect can be seen through the audience's brain wave response. This study is to examine the relationship between the movie story development and the movie story development through brain wave measurement of the emotional reaction of the audience in situations and events occurring in the movie development. Four American films, which represent each genre and are well known to many people, were selected for the study. These are of the adventure genre, of the animation genre, of the action genre, and of the drama genre. In order to measure the emotional response of these movies, four cases were set centered on the PPG of EEG and analyzed as a time series graph pattern. It can be seen that the emotional response on the graph has a certain relationship with the story development. It is expected that this study will help in selecting a genre when making a movie in the future, especially when deciding how to compose and develop a story, and it will help to induce the emotions of the audience.