• Cross-Cultural Studies
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• v.45
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• pp.433-478
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• 2016

This article investigates the role of Japan in Korean consumption of Nordic design. In spite of the development of greater access to wide information and global markets, the popular trends in Korea have been mediated by Japan. The cultural power of Japan comes from otaku subculture. Japanese influence can be discussed by two sides. One is the images or symbols composing the Nordic style in Korea. The other is the way how to consume the Nordic design. Japanese neopop images combined with the Nordic design. Japanese 'slow movie' has combined American Kinfolk style with Nordic style. 'Database consumption' from otaku subcultre conceptualized by Azma Hiroki can be applied to Korean consumption of Nordic design.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.131-138
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• 2013

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym, and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.297-309
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• 2012

The MPAA(Motion Picture Association of America) warned about serious problems of piracy due to nearly a quarter of all Internet traffic around the globe was related to Internet piracy. Thus, strong legal action is enforced for piracy over nationally through strengthen the copyright law. We in this paper conducted a survey to see whether netizens prefer to download just for the matter of their convenience. Our study becomes a motivation to consider about seriousness of piracy by comparing between Korea and foreign cases. To our surprise, the survey reveals that Korean netizens conspicuously aware of their downloading behaviors outpaces Canadian netizens. Canada lacks the basic protections for the digital environment and is a safe haven for Internet pirates.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.191-198
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• 2013

This study examined the importance of independent variables that affect users' preference on the VODs of the newly-released movies by using the conjoint analysis. The results demonstrated that 'price(44.6%)' is the most important variable, which is followed by 'device(24.5%)', 'recency(18.0%)', 'producing country(12.9%)'. Respondents obtained the relatively high utility from watching the VOD of a Korean movie currently on screen in 3,000 wons. A television set was the most preferable device for watching VODs. The traditional windowing strategy in the media content market has been recently challenged by the new trend that the holdback period between market windows is ignored and the high-priced content is found in the second window. Nevertheless, this study demonstrated that users of the VODs of the newly-released movies are still very sensitive to the price and consider 'the recency' to be relatively less important than 'price'.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.665-673
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• 2014

The Korean film market has revved up against American movies and the movie industry has continued to grow even though Korea is a small country. However, most production staffs who are responsible for practical business of film production get wages that fall short of the inflation rate and minimum wages as temporary employees. And there's the atmosphere that they try to leave film sites on the first opportunity. This study finds that the cause to leave film sites is attributed to perception gaps about the hardworking character and labor which occur in the process that production staffs enter the movie industry and participate in film production as well as poor surroundings. And it should establish staffs' hardworking character and recognition as workers to them by reorganizing the current curriculums which approach movies from the only artistic viewpoint in the departments related to movies and images that hold a large majority in their majors, establishing the concept of work according to participation in film production to potential production staffs, and changing their recognition to improve the elements that they leave the sites.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.298-305
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• 2009

In contrast to content_based filtering systems, collaborative filtering systems not only don't contain information of items, they can not recommend items when users don't provide the information of their interests. In this paper, we propose the recommender agent using association item tree to solve the shortcomings of collaborative filtering systems. Firstly, the proposed method clusters users into groups using vector space model and K-means algorithm and selects group typical rating values. Secondly, the degree of associations between items is extracted from computing mutual information between items and an associative item tree is generated by group. Finally, the method recommends items to an active user by using a group typical rating value and an association item tree. The recommender agent recommends items by combining user information with item information. In addition, it can accurately recommend items to an active user, whose information is insufficient at first rate, by using an association item tree based on mutual information for the similarity between items. The proposed method is compared with previous methods on the data set of MovieLens recommender system.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.65-73
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• 2020

Viral video advertising is being used in the advertising and film industry for pre-promotion of certain products or pre-release films which has a lot of effect on investment. An analysis of viral video recognition is needed to predict future development directions. In response, the study conducted a survey on viral videos, focusing on college students in their 20s, who are the most exposed to advertisements and movies. Through this, the survey was conducted on recognition of viral videos, memorable viral videos, satisfaction level, message propagation method, positiveness of viral videos, expected future development, and desired viral video type. The survey showed that viral video recognition was 16.7% and the most memorable viral video; the "Let it Go" viral video from the movie "Frozen" was 69.1 %, according to the survey. The satisfaction level was not high at 31.2 %, and 73.5% of people sent messages to others after watching viral videos, which was very high. Negative opinions on viral videos were low at 13.7 %. 64.5% of the surveyors said the future of the viral videos would "develop" and 6.7% said would "not develop."

• The Research Journal of the Costume Culture
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• v.15 no.1 s.66
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• pp.13-24
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• 2007

This study measured the communication effect on the setting types and the exposure times to perform the effective PPL strategies. By the setting types(on-set and creative) and exposure times(short and long), 308 female older than 20 were divided into 4 experimental groups. Each groups were exposed to the edited movies and required to answer the questionaire. The data were analysed by SPSS 12.0 using Chi-Square, One-Way ANOVA and Duncan test. The results are as follows. First, in cognitive dimension, the on-set type and long exposure group showed the higher recognition and recall. Second, in emotional dimension, the signigicant difference was found in one brand(Kappa) of two which were used in the experiment. In this case, the on-set type and long exposure group showed the positive attitude toward the brand. Third, in behavioral dimension, there were no difference among the groups. The implications based on this results are as follows. First, when implementing of PPL the fashion brands in movies, the on-set type and long exposure would be the most effective method. Second, implementing IMC(Integrated Marketing Communication) linked to the PPL strategy can be more effective. In contrast to the other product categories, it is hard to recognize the brand of fashion goods if the logo or the brand name is not exposed directly. Therefore Combining other communication strategies such as press release simultaneously will birng the more effective result of PPL in the movie.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.59-67
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• 2013

In this paper, we propose the LAR_CF, latent attribute rating-based collaborative filtering, that is robust to data sparsity problem which is one of traditional problems caused of decreasing rating prediction accuracy. As compared with that existing collaborative filtering method uses a preference rating rated by users as feature vector to calculate similarity between objects, the proposed method improves data sparsity problem using unique attributes of two target objects with existing explicit preference. We consider MovieLens 100k dataset and its item attributes to evaluate the LAR_CF. As a result of artificial data sparsity and full-rating experiments, we confirmed that rating prediction accuracy can be improved rating prediction accuracy in data sparsity condition by the LAR_CF.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.49-56
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• 2012

In this paper, we propose the method that decides the shot types using face detection technique. The shot types, such as close-up shot, medium shot, and long shot, can be applied as useful information for understanding narrative structure of movies. The narrative structure of movie is builded by characters. Also their mental and emotional changes become inextricably bound up with them of narrative. The shot types are decided by distance between character and camera. If put together above them, shot types can be found by using detection technique of face size of characters and understand narrative of movie. To do this, we propose the methodology to detect shot type by face detecting and implement the system to do it. Additionally, we evaluate the performance of the system. The implementation system has been evaluated as 95% for close-up shot detection and 90% for medium shot detection, while 53.3% is just detected for long shots.