• Journal of Digital Convergence
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• v.19 no.1
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• pp.327-333
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• 2021

The purpose of this study is to explore what elements and measures are necessary to grasp the content influence and competitiveness of each OTT platform, which is difficult to measure only with the existing TV broadcast ratings indicator, on the same basis. In this study, based on the RACOI, the daily Top 10 list provided by Netflix was scored to determine the correlation with the viewers' reaction to TV dramas, and a meaningful comparison criterion index was derived. Based on this, the study tried to analyze the share of content provided by the top 3 OTT platforms in Korea. Spearman's correlation analysis was performed for each indicator of RACOI and the Netflix popularity score. It was confirmed that the Netflix popularity score was correlated with the digital video views indicator of RACOI. As a result of analyzing the platforms, it was found that the popularity of the content provided by Netflix and Tving was relatively high. This study did not secure the company's sales data, and there is a limitation in that long-term tracking analysis could not be performed. However, the study extracted the viewer response indicators of TV that are correlated with popularity within Netflix. It is valuable as a basic study of an extended study that compares and confirms the long-term impact of content provided by each OTT platform in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.177-180
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• 2022

TV에서 OTT로 시청 수단이 변화하면서 스포츠 중계를 보는 젊은 층 시청자들이 줄어들고 있다. 또한 경기장으로 스포츠를 보러 오는 팬들도 점점 감소하는 추세이다. 이에 따라 스포츠 관계자들은 고정 팬 층의 흥미 증진과 신규 팬 층의 유입을 위해 스포츠 관전에 AR(증강 현실) 기술을 도입하고 있다. 모바일 활용과 직관에도 적용 가능한 AR에 대한 업계의 반응은 상대적으로 긍정적이다. 본 논문에서는 AR 스포츠 관전의 사례를 스포츠 중계와 경기장 관전으로 분류해 조사하고 향후 전망에 대해 알아본다. 그리고 AR 스포츠 관전의 활성화에 대한 방안을 제시한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.65-75
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• 2021

This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.342-364
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• 2014

The purpose of this paper is to provide an answer for the following question: What are the major shifts and implications of the unprecedently competitive and rapidly changing media ecosystem in the era of N-screen and OTT services? I've attempted to understand the complex and competitive nexus among media from an historical context by focusing on the displacement vs. complement thesis. The TPC model by Han has been employed for the analysis of the current dynamics of US media industries by triangulating three areas: Technology/industry, public policy and consumer/culture. More specifically, the US media landscape is initially divided into two competitive turfs - the competitors equipped with OTT services and the legacy media industry, and then the traditional media industry was grouped again into PayTV group(telecom service providers with IPTV and mobile TV, cable/Satellite TV networks) and Free (over-the-air) TV networks. Six major shifts were identified by the analysis: power shift in telecom carriers, power shifts in TV industry, Telecom/OTT partnership, time shifts, place shifts, and finally business model shifts.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.123-135
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• 2020

This study examined how the quality of Netflix service affects user satisfaction and continuance intention. This study classified the quality of Netflix service as content diversity, rate system appropriateness, recommendation system, N-screen service, binge viewing, and service quality, and examined the effect of each dimension on user satisfaction and continuous intention. We conduced an online survey on 202 Netflix users and analyzed the data with the SEM. Results are as follows. First, content diversity, recommendation system, binge-viewing and service quality are positively associated with user satisfaction. Second, the N-Screen service has neither direct nor indirect effects on continuance intention. However, rate system has a direct effect on continuance intention. On the other hand, content diversity, recommendation systems, binge-viewing, and quality of service affect continuance intention positively through user satisfaction. Finally, it is shown that user satisfaction and continuance intention have a significant static correlation as predicted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.87-89
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• 2022

Recently, as more consumers spend more time at home due to COVID-19, the time spent on digital consumption such as SNS and OTT, which can be easily used non-face-to-face, naturally increased. Since 2019, when COVID-19 occurred, digital consumption has doubled from 44% to 82%, and it is important to quickly and accurately grasp and apply trends by analyzing consumers' emotions due to the rapidly changing digital characteristics. However, there are limitations in actually implementing services using emotional analysis in small systems rather than large-scale systems, and there are not many cases where they are actually serviced. However, if even a small system can easily analyze consumer trends, it will help the rapidly changing modern society. In this paper, we propose a lightweight trend analysis system that builds a learning network through Transfer Learning (Fine Tuning) of the BERT Model and interlocks Crawler for real-time data collection.

• 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.

• Information and Communications Magazine
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• v.28 no.3
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• pp.19-26
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• 2011

본고에서는 스마트 TV의 대표적인 서비스인 OTT(Over-The-Top)서비스의 전송 방법 중 최근에 가장 주목을 받고 있는 HTTP에 기초한 적응적 스트리밍 기술을 알아본다. 먼저, 최근 MPEG등 각 표준단체에서 진행되고 있는 HTTP 스트리밍 기술의 표준화 범위 및 진행 상황에 대해서 살펴보고, 표준화 범위 중 핵심이 되는 메타데이타 파일 구조 및 청크 단위의 전송 포맷 및 기존 시스템 포맷의 확장 사항 등에 대해서 설명한다. 마지막으로 MPEG DASH(Dynamic adaptive streaming over HTTP)의 basic on-demand profile에 기초한 구현 내용 및 결과를 소개한다.

• Proceedings of the Optical Society of Korea Conference
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• 2000.08a
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• pp.248-249
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• 2000

최근 "혼돈제어"라는 몇 가지 방식이 증명되어 여러 시스템에서 혼돈스런 출렁임을 제거하게 되었다. 처음으로 OGY(Ott Grebogi Yorke) 방법에 기초를 둔 Occasional Proportional Feedback(OPF) 방식이 Roy에 의해 고체레이저 system 에 적용되었다$^{(1)}$ . 또 High Frequency Injection(HFI) 방식으로도 혼돈을 제어할 수 있음이 발표되기도 했다$^{(2),(3)}$ . 우리의 실험에서는 단일모드로 발진하는 Nd:YAG 레이저에서 일어나는 혼돈현상을 관측하려 한다. (중략)