• Journal of Korean Philosophical Society
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• v.137
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• pp.409-438
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• 2016

The movie, Battle of Wits which is based on the cartoon by Morihideki(森秀樹) is directed by Zhang Zhiliang(張之亮), a director from Hong Kong. Morihideki's cartoon is based on the novel by Sakemikenichi(酒見賢一). The movie represents a successful one-source multi-use case. Battle of wits, which deals with the Mozi's propaganda against war, presents the thought of Mozi School(墨家) in spring, autumn, and warring states. The movie criticizes aggressive war by powerful nations. Aggressive war is an extreme form of brutality and worthless action without any benefit. Aggressive war represents 'never each love(buxiangai, 不相愛)' and 'never each benefit(buxiangli, 不相利)' as understood by Mozi. The main character of the movie endeavors and successfully defends the enemy's attack as Mozi did. It is due to the propaganda of Mozi School 'not to attack(feigong, 非攻)' that they can defend themselves from the attack from a powerful nation. It means that 'the universal love(jianai, 兼愛)', the ideology of Mozi, is concretely actualized. The philosophy of Mozi School in the Battle of Wits has its limits as follows: the thought of Mozi School is just suitable during times of war and unnecessary in times of peace, the contradiction between universal love and hatred for one person; the Mozi School's faith in the nature of human beings to confront betrayal. This limit was also proposed in the movie. However, the movie presented how the masculinity of Mozi School, supplemented by the feminity of Daojia(道家), can succeed in achieving genuine communication. When focusing on this point, the movie can be interpreted as biased towards the philosophy of Daojia.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.285-294
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• 2020

"The Man Standing Next" was a 'anger-character movie' that shows a fierce psychological game between the characters. Inspired by this point, it was analyzed the narrative structure of this film based on scene unit applying the 'Five-stage Anger Model' formulated by Lakoff and Kövecses and others. The results showed that the causality and feasibility of the protagonist's anger behavior were highly reflected above the model. In particular, among the five steps, the film-maker spent the longest time on 'anger control' justifying the hero's motivation for punishment or retaliation, while giving the shortest time to 'loss of control' to maximize the urgentness of the punitive actions. The detonator causing his anger at each stage was disposed two to six times each stage with neglect, contempt, arrogance, ostentation, mockery, unauthorized intervention, etc. Sneering of "Chief Security Officer" and insulting of "The President" make the protagonist feel the scorn of a terrible friend-murderer each functioned as a "rage trigger." In conclusion, the film follows the above sophisticated model in its narrative structure. Though it was a political drama that sets up a lot of anger scheme caused from public reasons, it reflects ordinary people's routine anger, which corresponds to 24 percent of the list of Nobaco's Provocation Inventory (PI). The producers elaborately reflected the anger procedure theory and balanced the public and private drivers of rage. It was considered to be derived from the intention to enhance communication with the audience increasing their understanding and aspiration for political movie that are usually heavy and unfamiliar.

• Korean journal of communication and information
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• v.35
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• pp.147-178
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• 2006

Screen Quota is very important topic at our whole society not only film industry. Moreover the opinions are sharply divided. So, journalism, at the objective and neutral position, has the responsibility to present objective field to discuss and neutral information. This script censoriously focuses that how Korean Journalism handles Screen Quota issue from the upper mentioned premises. The first point is Korean Journalism gives legitimacy to the Governmental persistence, which is fixing Screen Quota as a hurdle for the FTA settlement so that it should be reduced. Secondly, Korean Journalism has been reducing the importance of the Screen Quota issue as the problem of film industry itself own, describing it as combat between Government and Film Industry. Third, it describes the Screen Quota as a privilege granted to the Film industry only. Finally, it provides power to the point of view of the Government which insists to reduce the Screen Quota mentioning the superiority of the competitiveness of the Koran Films discriminatingly. In conclusion, I could not but define that Korean Journalism is only speaking for America and Korean Government especially about the Screen Quota issue which is divided sharply. What it means is Korean Journalism has not been providing not only objective information but also impartial dispute field to the public for the issue which has very importance socially. The news and discussions about Screen Quota shows that this issue is not free from the progress of FTA which includes the Screen Quota problem. Further on, it could be deduced that the discussion about Korean film industry has kept on focusing its topic to the choice of decreasing or maintaining Screen Quota. The cultural contents have been expanding its importance day by day. Endeavors to settle the enormous problems of film industry should be preceded to strengthen the competitiveness and to prepare against market opening. Consequently, to solve the problems of film industry, Screen Quota should be positioned as a protect policy rather than a remedy for every ill, at the same time all the possibilities should be considered especially for the problems that Screen Quota could not solve.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.56-60
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• 2009

오늘날 인터넷은 개인의 감정, 의견을 서로 공유할 수 있는 공간이 되고 있다. 하지만 인터넷에는 너무나 방대한 문서가 존재하기 때문에 다른 사용자들의 감정, 의견 정보를 개인의 의사 결정에 활용하기가 쉽지 않다. 최근 들어 감정이나 의견을 자동으로 추출하기 위한 연구가 활발하게 진행되고 있으며, 감정 분석에 관한 기존 연구들은 대부분 어구의 극성(polarity) 정보가 있는 감정 사전을 사용하고 있다. 하지만 인터넷에는 나날이 신조어가 새로 생기고 언어 파괴 현상이 자주 일어나기 때문에 사전에 기반한 방법은 한계가 있다. 본 논문은 감정 분석 문제를 긍정과 부정으로 구분하는 이진 분류 문제로 본다. 이진 분류 문제에서 탁월한 성능을 보이는 Support Vector Machines(SVM)을 사용하며, 문서들 간의 유사도 계산을 위해 문장의 부분 문자열을 비교하는 문자열 커널을 사용한다. 실험 결과, 실제 영화평에서 제안된 모델이 비교 대상으로 삼은 Bag of Words(BOW) 모델보다 안정적인 성능을 보였다.

• 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 Advanced Navigation Technology
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• v.17 no.6
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• pp.792-797
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• 2013

4D film is just a film that made by adding some physical effects to 3D film or general film. In order to provide physical effects to the audience, the data that make the physical effect must be added to each frames. In this paper, we proposed a video detection system that can efficiently provide physical effects by assessing the present situation such as explosion scene, snowing scene. The proposed video detection system contains an algorithm for fire detection by using R color and $C_r$ value, and also an algorithm for snow detection by using RGB color model. The system constitutes in a MCU that from 8051 family. In the performance evaluations, the result shows that 91% of detection rate in case of fire and 25% of false detection rate in case of snow. Also the system is capable of providing physical effects automatically.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Proceedings of the Korean Fiber Society Conference
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• 2007.11a
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• pp.435-436
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• 2007

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• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.04a
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• pp.199-201
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• 2008

• 한국가스학회:학술대회논문집
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• 2006.11a
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• pp.183-186
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• 2006