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http://dx.doi.org/10.5392/JKCA.2020.20.04.001

What Do The Algorithms of The Online Video Platform Recommend: Focusing on Youtube K-pop Music Video  

Lee, Yeong-Ju (서울과학기술대 IT정책전문대학원)
Lee, Chang-Hwan (서울과학기술대 데이터사이언스학과 일반대학원)
Publication Information
The Journal of the Korea Contents Association / v.20, no.4, 2020 , pp. 1-13 More about this Journal
Abstract
In order to understand the recommendation algorithm applied to the online video platform, this study examines the relationship between the content characteristics of K-pop music videos and related videos recommended for playback on YouTube, and analyses which videos are recommended as related videos through network analysis. As a result, the more liked videos, the higher recommendation ranking and most of the videos belonging to the same channel or produced by the same agency were recommended as related videos. As a result of the network analysis of the related video, the network of K-pop music video is strongly formed, and the BTS music video is highly centralized in the network analysis of the related video. These results suggest that the network between K-pops is strong, so when you enter K-pop as a search query and watch videos, you can enjoy K-pop continuously. But when watching other genres of video, K-pop may not be recommended as a related video.
Keywords
Contents Recommendation System; Algorithm; Online Video Platform; Related Video;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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