• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.47-50
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• 2017

PC 혹은 모바일 환경이 점점 발전됨에 따라 사용자들은 자신의 목적에 맞는 다양한 콘텐츠들을 쉽게 이용하고 있다. 사용자는 정상적인 콘텐츠를 이용할 경우 콘텐츠가 가지고 있는 태그정보를 통해 콘텐츠의 내용을 식별하여 사용한다. 하지만 올바른 태그정보가 들어있지 않은 콘텐츠의 경우 사용자는 잘못 입력된 태그정보로 인해 콘텐츠를 식별하는 과정에서 어려움을 겪을 수 있는 문제점을 가지고 있다. 본 논문에서는 사용자가 가지고 있는 콘텐츠에 접근하여 스마트폰 혹은 PC에 저장되어있는 다양한 콘텐츠들을 유튜브 API를 통해 유튜브 플랫폼에 존재하는 영상들과 매칭 시키고, 매칭 시킨 영상들을 사용자 계정에 동기화시키는 시스템을 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.187-188
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• 2023

본 논문에서는 안드로이드 플랫폼 기반의 스마트폰에 내장된 GPS 센서와 카카오 로그인 API, 기상청 API, 유튜브 라이브러리, 크롤링을 활용한 체감 온도 기반 코디 추천 애플리케이션을 설계하고 구현한다. 카카오 로그인 API를 활용한 제삼자 로그인 인증 방식을 사용하고 사용자별 체질 정보를 입력받아 개인화된 옷차림 정보를 제공하도록 구현한다. 또한 GPS 센서로 받아온 위치 정보를 기상청 API와 연동하여 사용자의 현재 위치에 해당하는 날씨 정보와 체감 온도를 계산하여 제공하도록 구현한다. 그리고 유튜브 라이브러리를 사용하여 유튜브 코디 영상을 제공하여 사용자의 코디에 도움을 주도록 구현한다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.129-132
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• 2009

본 논문은 오픈 API를 이용하여 다국어 정보검색 시스템을 모델링하는 방법론을 제시한다. 웹 2.0이 대두되면서 웹 2.0의 개념을 활용한 기술들이 발달하고 있는데, 그 중 한 기술이 오픈 API이다. 기업에서 개발한 새로운 서비스나 기능, 데이터 등을 API로 공개함으로써 사용자들이 공개된 API를 이용하여 새로운 서비스를 쉽게 개발할 수 있게 되었다. 본 연구에서는 구글, 플리커, 유튜브, 네이버, 다음 등의 사이트에서 제공하는 오픈 API를 이용하여, 다국어 정보 검색 시스템을 구현하였다. 구글 번역 API를 이용하여 한국어 질의어를 검색 대상 언어(영어, 일본어, 중국어 등)로 번역한 후, 소설 웹 사이트(플리커, 유튜브, 다음, 네이버 등)의 정보를 검색하고, 검색된 결과 내 텍스트를 다시 한국어로 번역한 후, 통합된 검색 결과를 사용자에게 보여준다.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.169-186
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• 2020

This study aims to examine the characteristics of news content and users' reactions in local broadcasting Youtube news' channel, and explore how the local media should response in the new online video environment. YouTube Open API sampled 3,950 news-related videos uploaded over a month on 31 YouTube news channels nationwide. The content analysis was performed on the basis of the analysis of individual videos, such as characteristics of each content and users' reactions. As a result, a few news channels have produced digital-only content, but the ratio has been very low, most were broadcast replay videos with titles and formats uploaded as they were. In some cases, it still operates as a comprehensive channel, which failed to show its expertise as an independent digital news platform. This shows that theses YouTube channels lacks differentiation from TV or its own web page, and is still skewed to the auxiliary role or online archive function of TV platform. Nevertheless, digital-only content, which can be a national issue based on regional expertise, has led to a higher number of views and users reactions, suggesting that is a realistic and effective strategy with expandability in online space in the future.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.49-55
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• 2023

In this study, models for predicting the popularity of mukbang content on YouTube were proposed, and factors influencing the popularity of mukbang content were identified through post-analysis. To accomplish this, information on 22,223 pieces of content was collected from top mukbang channels in terms of subscribers using APIs and Pretty Scale. Machine learning algorithms such as Random Forest, XGBoost, and LGBM were used to build models for predicting views and likes. The results of SHAP analysis showed that subscriber count had the most significant impact on view prediction models, while the attractiveness of a creator emerged as the most important variable in the likes prediction model. This confirmed that the precursor factors for content views and likes reactions differ. This study holds academic significance in analyzing a large amount of online content and conducting empirical analysis. It also has practical significance as it informs mukbang creators about viewer content consumption trends and provides guidance for producing high-quality, marketable content.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.189-192
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• 2021

YouTube, the world's largest video sharing platform, is loved by many users in that it provides numerous videos and makes it easy to get helpful information. However, the ratio of like/hate for each video varies according to the subject or upload time, even though they are in the same channel; thus, previous studies try to understand the reason by inspecting some numerical statistics such as the ratio and view count. They can help know how each video is preferred, but there is an explicit limitation to identifying the cause of such preference. Therefore, this study aims to determine the reason that affects the preference through matching between topic words extracted from comments in each video and non-sympathetic types defined in advance. Among the top 10 channels in the field of 'pets' and 'cooking', where outliers occur a lot, the top 10 videos (the threshold of pet: 4.000, the threshold of cooking: 0.723) with the highest ratio were selected. 11,110 comments collected totally, and topics were extracted and matched with non-sympathetic types. The experimental results confirmed that it is possible to predict whether the rate of like/hate would be high or which non-sympathetic type would be by analyzing the comments.

• Korean Association of Arts Management
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• no.57
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• pp.59-84
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• 2021

This study examined the structure of YouTube video network and the factors for the diffusion of Chinese creator's videos through the case of famous Chinese creator Fengtimo. There is few interest to the diffusion of Chinese contents among Korean researchers, while they have been studied the consumption of Hallyu(Korean wave) contents overseas. Using the data that YouTube Data API offers, this study analysed the video network that the comments of which are same users with NodeXL tools and the regression model with JASP tools. The study found that there are three groups of the YouTube channels of that network. They are domestic official accounts of Fengtimo, foreign officail accounts of Fengtimo and individual creators' accounts. The official accounts share the videos of Fengtimo's songs and entertainment contents for the fans, where the individual creators share their own meme videos(UGC). The significant factors for the diffusion in the YouTube video network are comments, likes, out-degree, dislikes, in-degree and betweenness centrality. There are significant difference between official channel and indivisual groups on the views. And degree and betweenness centrality have mediating effect. It is necessary to conduct more research on that subject with many other cases if we want to get to know the generalized explanation.