• Title/Summary/Keyword: OTT content

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A Study on the Experiential Response of Short-Form Video Users

  • Lim, Dong Kyun
    • International journal of advanced smart convergence
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    • v.10 no.4
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    • pp.273-277
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    • 2021
  • As society gradually enters a virtual, non-face-to-face society, the use of online content is increasing as well. In particular, as smartphones are thoroughly established in our daily life, the platforms of webtoons, mobile broadcasting, and education are shifting from personal computers to smartphones. Recently, the development of the Over-The-Top media service (OTT service) enabled streaming services of various media contents through the internet and activation of IPTV. Therefore, the rapid increase of popularity of short-form content is a natural phenomenon with smartphone platforms with fast, improvised, and endless communication. Lately, TikTok became the favored platform with prosumers, defined as people who are both producers and consumers. In this study, I studied the experiential response of YouTube and TikTok users as representative examples of a short-form content platform developed after the 2000s, the flourishing years of digital content with a length of 30 seconds.

Efficient Illegal Contents Detection and Attacker Profiling in Real Environments

  • Kim, Jin-gang;Lim, Sueng-bum;Lee, Tae-jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.6
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    • pp.2115-2130
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    • 2022
  • With the development of over-the-top (OTT) services, the demand for content is increasing, and you can easily and conveniently acquire various content in the online environment. As a result, copyrighted content can be easily copied and distributed, resulting in serious copyright infringement. Some special forms of online service providers (OSP) use filtering-based technologies to protect copyrights, but illegal uploaders use methods that bypass traditional filters. Uploading with a title that bypasses the filter cannot use a similar search method to detect illegal content. In this paper, we propose a technique for profiling the Heavy Uploader by normalizing the bypassed content title and efficiently detecting illegal content. First, the word is extracted from the normalized title and converted into a bit-array to detect illegal works. This Bloom Filter method has a characteristic that there are false positives but no false negatives. The false positive rate has a trade-off relationship with processing performance. As the false positive rate increases, the processing performance increases, and when the false positive rate decreases, the processing performance increases. We increased the detection rate by directly comparing the word to the result of increasing the false positive rate of the Bloom Filter. The processing time was also as fast as when the false positive rate was increased. Afterwards, we create a function that includes information about overall piracy and identify clustering-based heavy uploaders. Analyze the behavior of heavy uploaders to find the first uploader and detect the source site.

An Exploratory Study of Psychological Characteristics of Metaverse Users (메타버스 이용자의 심리 특성 탐색 연구)

  • Hyeonjeong Kim;HyunJung Kim;Beomsoo Kim;Hwan-Ho Noh
    • Knowledge Management Research
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    • v.24 no.4
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    • pp.63-85
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    • 2023
  • This study aims to identify the primary user group in the growing metaverse space based on the increased interest during the COVID-19 era. It also aims to explore the predictive factors for metaverse adoption. To predict online activities, the study examined user purposes, motivations, and relevant demographic factors as predictive variables through model analysis. The data from the Korean Media Panel Survey were used, and a two-stage analysis with the Heckman two-stage sample selection model was conducted to predict metaverse users. The analysis revealed that the key factors influencing metaverse adoption were offline activities, openness, OTT usage, and purchasing of paid content. Moreover, in the second stage model, openness, gender, and paid content purchases were identified as significant variables for increasing metaverse usage time. These results indicate that understanding metaverse users is essential in the context of the rising interest in online activities during the COVID-19 era and can provide valuable insights for metaverse platform-related companies and developers.

A Study on the Proposal of Spiral Evolution Model of IPTV, M-IPTV, OTT & Smart Media focusing on Exploration & Exploitation Theory (IPTV, M-IPTV, OTT, 스마트미디어 진화단계에 관한 탐색과 활용관점의 Spiral 모형 연구)

  • Lee, Sang-Ho;Kim, Jai-Beom;Kim, Young-Berm
    • Journal of Digital Contents Society
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    • v.15 no.3
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    • pp.327-338
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    • 2014
  • This study proposes the evolution model of emerging media platform including smart media (M-IPTV, Smart TV) and IPTV, through a spiral evolution model based on the theory of the exploration & the exploitation. Authors suppose that the IP media evolved from IPTV technology, evolution of which has come through the development model of serial circular process. For explanation of this evolution, we propose the research model integrating the spiral model and the exploration & exploitation theory. Researchers define the smart media as the evolved media from IPTV, through this proposed model. We expect this model to be the theoretical base of media regulation and setting direction of future media service. Thus, this research are summed up as follows. To begin with, we classify the evolutionary stage of IPTV from the view points of service feature, regulation frame and technological characters. Secondly, we organize and confirm the research model of IPTV evolution through case analysis of the 3 cycles of each evolutionary stage. As a result, discussion of this study helps understanding mobile IP media and smart media as a post IPTV and leads the solution of various regulation issues and the development of the innovative media service and content. In addition, it can guide the government for the evolutionary direction to promote the media and the content industry.

Metadata extraction using AI and advanced metadata research for web services (AI를 활용한 메타데이터 추출 및 웹서비스용 메타데이터 고도화 연구)

  • Sung Hwan Park
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.499-503
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    • 2024
  • Broadcasting programs are provided to various media such as Internet replay, OTT, and IPTV services as well as self-broadcasting. In this case, it is very important to provide keywords for search that represent the characteristics of the content well. Broadcasters mainly use the method of manually entering key keywords in the production process and the archive process. This method is insufficient in terms of quantity to secure core metadata, and also reveals limitations in recommending and using content in other media services. This study supports securing a large number of metadata by utilizing closed caption data pre-archived through the DTV closed captioning server developed in EBS. First, core metadata was automatically extracted by applying Google's natural language AI technology. The next step is to propose a method of finding core metadata by reflecting priorities and content characteristics as core research contents. As a technology to obtain differentiated metadata weights, the importance was classified by applying the TF-IDF calculation method. Successful weight data were obtained as a result of the experiment. The string metadata obtained by this study, when combined with future string similarity measurement studies, becomes the basis for securing sophisticated content recommendation metadata from content services provided to other media.

Automatic Generation of Video Metadata for the Super-personalized Recommendation of Media

  • Yong, Sung Jung;Park, Hyo Gyeong;You, Yeon Hwi;Moon, Il-Young
    • Journal of information and communication convergence engineering
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    • v.20 no.4
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    • pp.288-294
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    • 2022
  • The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

Community Model for Smart TV over the Top Services

  • Pandey, Suman;Won, Young Joon;Choi, Mi-Jung;Gil, Joon-Min
    • Journal of Information Processing Systems
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    • v.12 no.4
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    • pp.577-590
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    • 2016
  • We studied the current state-of-the-art of Smart TV, the challenges and the drawbacks. Mainly we discussed the lack of end-to-end solution. We then illustrated the differences between Smart TV and IPTV from network service provider point of view. Unlike IPTV, viewer of Smart TV's over-the-top (OTT) services could be global, such as foreign nationals in a country or viewers having special viewing preferences. Those viewers are sparsely distributed. The existing TV service deployment models over Internet are not suitable for such viewers as they are based on content popularity, hence we propose a community based service deployment methodology with proactive content caching on rendezvous points (RPs). In our proposal, RPs are intermediate nodes responsible for caching routing and decision making. The viewer's community formation is based on geographical locations and similarity of their interests. The idea of using context information to do proactive caching is itself not new, but we combined this with "in network caching" mechanism of content centric network (CCN) architecture. We gauge the performance improvement achieved by a community model. The result shows that when the total numbers of requests are same; our model can have significantly better performance, especially for sparsely distributed communities.

Analyzing Sport Documentary Online - Focus on All or Nothing: Manchester City on Prime Video

  • Han, Sukhee
    • International journal of advanced smart convergence
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    • v.8 no.3
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    • pp.20-26
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    • 2019
  • This study multi-dimensionally analyzes a sport documentary, All or Nothing: Manchester City, which is an original content on Prime Video, an American Over-The-Top (OTT) platform. Due to the success of South Korean soccer player Heung-min Son who plays Tottenham Hotspur of England, the popularity of the English Premier league is recently the greatest in South Korea along with the fact that soccer has been a popular sport for a long time. This study focuses on the success of the soccer club, Manchester City, which has become a rising star with its huge investment from United Arab Emirates; Manchester City won the league four times since 1992/1993 season. Also, during the 2017/2018 season, the background the documentary, Manchester City won the league title with new records, which shows the greatness of Manchester City. Especially, this study examines the documentary by 1) Story 2) Type of Scene 3) How to watch. Thus, this study explores not only the aspects of team-themed sport documentary that shows how and why Manchester City is excellent, but also the traits of the original content that explores the structure of the media platform.

The Impact of User Behavior, Contents, Function, Cost on Use Satisfaction and the Continued Use Intention of the N-screen Service Users (N 스크린 서비스의 이용행태, 콘텐츠, 기능, 비용이 이용 만족도와 지속이용의사에 미치는 영향에 관한 연구)

  • Kim, Dong-Woo;Lee, Yeong-Ju
    • Journal of Broadcast Engineering
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    • v.18 no.5
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    • pp.749-757
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    • 2013
  • This study aims to find out the influences of user behavior, content characteristics, functional factors and user's perception in cost on user satisfaction and continuous intention in N-Screen service. Web survey was conducted for 498 users who have used N screen service. The results show that the most influential factor contributing to user satisfaction is user interface. VOD diversity, payment system, cost, channel diversity are also meaningful factors. Identifying the critical factors which impact on user satisfaction, this study can provide the basic data for activating OTT service in smart media environment.

The Effect of Consumer's Personality on the Selection Factor for Movie Channel and Channel Attitude (소비자의 성격이 영화 채널 선택 요인과 채널 태도에 미치는 영향)

  • Lim, Gyoo Gun;Kim, Boyoung Renee;Cho, Sung Min;Song, Ni Eun
    • The Journal of the Korea Contents Association
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    • v.19 no.7
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    • pp.348-359
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    • 2019
  • In recent years, movie content consumption has increased not only in theaters but also through online channels. As movie channels become more diverse, there is a growing interest in movie channel selection process, and the movie channel selection can vary depending on the characteristics of consumers. Therefore, in this study, we examined the effect of consumer personality(neurogenic, conscientiousness, openness, agreeableness) on channel selection factors(primary and secondary factors of the theater, primary and secondary factors of online channel) and channel attitudes(attitudes towards theaters, IPTV, cable TV, OTT). The results of this study shows that consumer personality has significant impact on consumers' movie channel selection process and findings provide strategic directions for companies offering online and offline service for movie consumption.