• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.64-79
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• 2022

The concept of Virtual Character has been developed for a long time with people's demand for cultural and entertainment products such as games, animations, and movies. In recent years, with the rapid development of concepts and industries such as social media, self-media, web3.0, artificial intelligence, virtual reality, and Metaverse, Virtual Character has also expanded new derivative concepts such as Virtual Idol, Virtual YouTuber, and Virtual Digital Human. With the development of technology, people's life is gradually moving towards digitalization and virtualization. At the same time, under the global environment of the new crown epidemic, human social activities are rapidly developing in the direction of network society and online society. From the perspective of digital media content, this paper studies the production technology of Virtual Character related products in the Chinese market, and analyzes the future development direction and possibility of the Virtual Character industry in combination with new media development directions and technical production methods. Consider and provide reference for the development of combined applications of digital media content industry, Virtual Character and Metaverse industry.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.77-83
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• 2019

Recently, as social media users have grown, the resulting form of advertising has emerged, and one of the types is native advertising. This advertising method appears to be 52% higher than the banner, according to a study by the IPG Media Lab (2013). Therefore, there is a positive effect on native advertising, but it is necessary to maximize the effect. In this paper, the acceptor's attitude to the native advertisement and the shared intention are verified as to how the effect of the native advertisement can be understood and the maximized effect can be obtained. When the brand phrase was in the form of direct exposure, the subjects were positive about the advertisement and the brand attitude was favorable. Share intentions were also high. These results included suggestions to produce native advertisements in consideration of the attitudes and sharing of the recipients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3023-3036
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• 2019

This study investigated the television (TV) content viewers' behavior influenced by online communication at the choice of new TV series on a terrestrial streaming platform. For exploring the impact of the anchoring effect on the TV content consumption, this study analyzed the correlation between the first episode's TV ratings and the data of online comments or reactions. These data were potential audiences' communication, which were generated on the online article three weeks before the first broadcasting began. To avoid the crucial influence by external factors, such as season and social issue, the test was done with eight (8) TV series which have same genre (drama), similar core audience targeting (20-49's women), similar broadcasting period (Jun-Oct 2016), same scheduling (10.00 to 11.00 pm, weekdays) and aired on terrestrial TV platforms. This research found that not only the amount of comments and reactions, but also the attitude about the comments created before broadcasting, positively influence the audiences' decision-making behavior for new TV content choices. This investigation contributes to the literature on media economics and management by exploring the media content users' consuming behavior with behavioral economics perspectives (anchoring effect) and making a first step for finding a new effect on the media content consumption.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.308-309
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• 2011

최근 소셜 미디어(Social Media)라는 말은 컴퓨터 관련 연구분야에 종사하는 사람들 뿐만 아니라 일반 사람들도 모르는 사람이 없을만큼 중요하고, 많이 쓰이는 말이다. 본 연구에서는 인터넷과 통신기기의 발달로 이러한 소셜 미디어들이 사용자들이 감당할 수 없을 만큼 생성되지만 이러한 소셜 미디어를 어떻게 사용하고 효율적으로 묶어서 표현해야 하는지에 관한 연구이다. 소셜미디어의 종류에는 블로그, 소셜 네트워킹 서비스(SNS), 위키, UCC, 마이크로 블로그 등으로 나누어진다. 본 연구에서는 Social Media를 기반으로 Tangible Blog를 위한 콘텐츠를 저작하는 시스템에 관한 연구를 진행한다. 여기서 소셜미디어는 일반적으로 사용되는 사진, 동영상, 효과음, 텍스트에 3D Contents를 추가는 것을 목표로 한다. 3D Contents는 현재 게임분야에 많이 사용되고 있는 Kinect를 이용하여 생성하고 이러한 소셜 미디어들을 Web 환경에서 Authoring 하는 방법에 관한 연구를 소개한다. 최종적으로는 현재 많이 사용되고 있는 Blog의 형태에서 발전한 Tangible Blog를 만드는 것이 목표이다. 여기서 Tangible Blog는 기존의 텍스트, 음악, 동영상 등의 소스를 이용한 사용자의 일상생활 및 의견 표현을 넘어선 3D Contents의 활용, 스토리텔링 기법 활용 및 Sensory Effect를 활용한 실감 있는 블로그를 만드는 것을 목표로 한다.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.40-52
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• 2018

Media can be considered as a type of play for kids in this new media era. Researches on media content for kids have mainly focused on educational effect or specific features such as design, but a great deal of kids content is created for fun and enjoyment. This study analyzes fun factors of the most popular kids content on Youtube: Kongsuni and Friends, Carrie and Toys, and Pinkfong. The result shows that seven fun factors can be grouped into three categories; 1) Self-determination and independence are related to the media environment; 2) Sensuous vividness, empathy, and physical dynamic are related to the content; 3) Self-expression and social interaction are related to associated activities. This study extends our perspective on kids content by analyzing fun factors in the comprehensive process of media consumption.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.9-15
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• 2019

The government has defined domestic violence as one of the four major social evils and tried to prepare laws and systems to prevent it. Nevertheless, domestic violence has emerged as a serious social issue, and compare to the number of domestic violence cases that are constantly increasing, the report rate of domestic violence is significantly lower. This suggests the need to improve citizens' perception of domestic violence as the issue to solve it together in society, not as a private matter at home. Most of existing contents for preventing domestic violence and improving awareness are simple viewing forms of video contents, which have little effect on recognition. We aim to confirm the possibility of improving social awareness about domestic violence by producing Virtual Reality (VR) contents that have great features of user's immersion and empathy. In this VR content, the user can interact with various objects in the virtual reality of domestic violence and directly or indirectly experience the victim's position. Users who view the violent environment from the victim's point of view can have a subjective empathy for the problem, which is expected to induce more active awareness about domestic violence.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.79-88
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• 2024

The use of the social media has become part of our daily life activities. The social web channels provide the content generation facility to its users who can share their views, opinions and experiences towards certain topics. The researchers are using the social media content for various research areas. Sentiment analysis, one of the most active research areas in last decade, is the process to extract reviews, opinions and sentiments of people. Sentiment analysis is applied in diverse sub-areas such as subjectivity analysis, polarity detection, and emotion detection. Stance classification has emerged as a new and interesting research area as it aims to determine whether the content writer is in favor, against or neutral towards the target topic or issue. Stance classification is significant as it has many research applications like rumor stance classifications, stance classification towards public forums, claim stance classification, neural attention stance classification, online debate stance classification, dialogic properties stance classification etc. This research study explores different feature sets such as lexical, sentiment-specific, dialog-based which have been extracted using the standard datasets in the relevant area. Supervised learning approaches of generative algorithms such as Naïve Bayes and discriminative machine learning algorithms such as Support Vector Machine, Naïve Bayes, Decision Tree and k-Nearest Neighbor have been applied and then ensemble-based algorithms like Random Forest and AdaBoost have been applied. The empirical based results have been evaluated using the standard performance measures of Accuracy, Precision, Recall, and F-measures.

• Journal of Distribution Science
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• v.22 no.8
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• pp.109-124
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• 2024

Purpose: This study examines short-platform content that is becoming more popular on social media. This study investigates the relationship between short-form content experience, consumer participation behavior, and consideration set. Furthermore, the mediating effect on empathy factors was confirmed during consumers' experience with short-form content. Data and methodology: Prior studies were reviewed, and hypotheses were developed. Consumers who had watched and shared short-form content within the previous three months were targeted to achieve the study's goal. A structured questionnaire was used to conduct the survey. Results: First, users of short-platform content with practical, playful, and emotional value did not confirm a positive effect on consumer participation behavior. However,short-form content with social value positively impacted consumer participation behavior. Second, consumer participation in short-form content was confirmed to positively affect the consideration set. Third, in terms of the mediating effect of empathy factors, short-platform content with practical, social, and emotional values partially mediates consumer participation behavior, whereas short-platform content with playfulness value completely mediates consumer participation behavior. Conclusions: The results of this study have academic and practical implications for the recent marketing field. In particular, research has been conducted in the field of digital marketing, which has recently changed rapidly.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.332-337
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• 2023

The purpose of the study was to analyze consumers' perceptions of gamification. Based on the analyzed data, we would like to provide data by systematically organizing the concept, game elements, and mechanisms of gamification. Recently, gamification can be easily found around medical care, corporate marketing, and education. This study collected keywords from social media portal sites Naver, Daum, and Google from 2018 to 2023 using TEXTOM, a social media analysis tool. In this study, data were analyzed using text mining, semantic network analysis, and CONCOR analysis methods. Based on the collected data, we looked at the relevance and clusters related to gamification. The clusters were divided into a total of four clusters: 'Awareness of Gamification', 'Gamification Program', 'Future Technology of Gamification', and 'Use of Gamification'. Through social media analysis, we want to investigate and identify consumers' perceptions of gamification use, and check market and consumer perceptions to make up for the shortcomings. Through this, we intend to develop a plan to utilize gamification.