• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.101-112
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• 2017

The purpose of this study was to examine the factors affecting innovation resistance and intention of use of social TV non-users focused on innovation diffusion theory and innovation resistance model. The results were as follows: First, compatibility among perceived innovation characteristics by social TV non-users influenced negatively on innovation resistance, and complexity among perceived innovation characteristics by social TV non-users influenced positively on innovation resistance. Second, perceived risk by social TV non-users influenced positively on innovation resistance. Third, compatibility among perceived innovation characteristics by social TV non-users influenced positively on social TV intention to use. And complexity among perceived innovation characteristics by social TV non-users influenced negatively on social TV intention to use. Fourth, perceived risk by social TV non-users influenced not significantly on social TV intention to use. Fifth, innovation resistance by social TV non-users influenced negatively on social TV intention to use.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.801-806
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• 2016

The purpose of this study was to examine the relationship between the determinant factors of social TV resistance to innovation and intention to use focused on college students. The results were as follows. First, complexity, trialability and observability among the determinant factors of social TV usage influenced positively on resistance to innovation of social TV, and complexity influenced negatively on resistance to innovation of social TV. Second, only observability among the determinant factors of social TV usage influenced positively on intention to use. Third, resistance to innovation of social TV usage influenced negatively on intention to use.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.268-272
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• 2009

Reportedly it says that 45% teenagers in the United State exchange the SMS with their friends during television watching. In other word TV viewing moulds the social community between audiences. In terms of social television it is all about interaction or communication technology relevant to TV watching as well as social behaviour. Besides it integrates voice communication, text chat, context awareness, TV recommendations, ratings, video conference and so forth. So far it approaches the conceptual stage or pilot production and remains more research and development. This study is to scrutinise whether the functionality of social TV enables to substitute for social activities of TV viewers or not.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.73-75
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• 2010

Current communication and broadcasting services are moved to integrated convergence service. So IPTV(Internet Protocol based TeleVision) services are growth rapidly. Traditional TV were provide simplex service. but IPTV will provide duplex service that is possible of interaction with TV and audience. Therefore current researches are focusing the Social TV service. at this point, we see the trend of Social TV system for research and implementation.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.243-261
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• 2021

Social TV users and content are increasing day by day. The main purpose was to study the motivation for social television users, but I felt the need to analyze the potential psychological impact of users in various content. This study analyzed the impact on psychological well-being due to the interaction and viewing satisfaction by the object relations theory factors of social TV user in Korea. A survey was conducted on students of N university, ordinary university, and ordinary people who have experience using social TV to prove the observations or experiments of empirical facts in this study. Research result, First, Nonalienation have been have a positive effect on interaction and viewing satisfaction. Second, stable attachment have been have a positive effect on interaction. Third, social competence have been have a positive effect on interaction. Fourth, interaction have been have a positive effect on viewing satisfaction and psychological well-being. Fifth viewing satisfaction have been have a positive effect on Psychological well-being. Through this, This will contribute to the development of subdivided content and user-customized services for social television, and it is necessary to reconfigure and study various events that may occur between users in the future.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.155-156
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• 2013

소셜 TV 사용 시, 사용자들은 TV를 시청하면서 타 사용자와의 소통을 위해 리모컨을 이용해서 텍스트를 작성해야하는 불편함을 가지고 있다. 본 논문에서는 소셜 TV의 이러한 불편함을 해결하기 위해 사용자 반응 사운드를 자동으로 인식하여 상대방에게 이모티콘을 전달하기 위한 시스템을 제안하며, 사용자 반응 사운드 인식에 사용되는 분류방식들을 비교한다. 사용자 반응 사운드 인식을 위해 사용되는 분류 방식들 중에서, Gaussian Mixture Model(GMM), Gaussian Mixture Model - Universal Background Model(GMM-UBM), Hidden Markov Model(HMM), Support Vector Machine(SVM)의 성능을 비교하였다. 각 분류기의 성능을 비교하기 위하여 MFCC 특징값을 각 분류기에 적용하여 사용자 반응 사운드 인식에 가장 최적화된 분류기를 선택하였다.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.1-22
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• 2022

We investigate the dynamic relationships among digital piracy activities, TV ratings, and online buzz for Korean TV dramas using a panel vector autoregression model. Our main findings include 1) TV ratings are negatively affected by digital piracy activities but positively affected by google buzz, 2) digital piracy activities are negatively affected by TV ratings and social buzz, and 3) social buzz and google buzz are positively influenced by each other. While many empirical studies were conducted to reveal the effects of music or movie piracy, our understanding of drama piracy is limited. We provide empirical evidence of the dynamic relationships between drama piracy, TV ratings, and online buzz. Our findings show the presence of indirect piracy effects on TV ratings through online buzz. Further, we reveal that social buzz and google trends play different roles in promoting TV ratings and piracy activities. We discuss the implications of our findings for theory and practitioners.

• Cartoon and Animation Studies
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• s.44
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• pp.285-306
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• 2016

With the increase use of smartphones, users can consume contents such as webtoon, webnovel and TV drama directly provided by the producers. In this Direct-to-Consumer era, webdrama services from the portal websites are increasing rapidly. Webdramas such as , , and can be analyzed in real time using responses such as unique users, likes, and comments. The analyses used in this research were Social Media Big Data Mining Method and Opinion Mining Method. Specific key words from webdrama can be extracted and viewers positive, neutral or negative emotion can be predicted from the words. The analyses of popular webdramas showed that the established K-Pop Idol member appearance and servicing portal site greatly influence the views, traffics, comments, and likes. Also, 'Mobile TV' proved the effectiveness as another platform other than television. Mobile targeted contents and robust business models still to be developed and identified. Overcoming these few tasks, Korea will be proven to be a webdrama content powerhouse.

• The Magazine of Kiice
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• v.11 no.2
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• pp.33-39
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• 2010

• Journal of Digital Convergence
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• v.12 no.3
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• pp.255-261
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• 2014

Advances of digital device technology such as digital cameras, smart phones and tablets, provide convenience way for people to take pictures during his/her life. Photo data is being spread rapidly throughout the social network, causing the excessive amount of data available on the internet. Photo retrieval is categorized into three types, which are: keyword-based search, example-based search, visualize query-based search. The commonly used multimedia search methods which are implemented on Smart TV are adapting the previous methods that were optimized for PC environment. That causes some features of the method becoming irrelevant to be implemented on Smart TV. This paper proposes a novel Visual Query-based Photo Retrieval Method in Smart TV Environment using a motion sensing input device known as Kinect Sensor. We detected hand gestures using kinect sensor and used the information to mimic the control function of a mouse. The average precision and recall of the proposed system are 81% and 80%, respectively, with threshold value was set to 0.7.