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

온라인 동영상 플랫폼의 알고리듬은 어떤 연관 비디오를 추천하는가: 유튜브의 K POP 뮤직비디오를 중심으로

  • 이영주 (서울과학기술대 IT정책전문대학원) ;
  • 이창환 (서울과학기술대 데이터사이언스학과 일반대학원)
  • Received : 2020.02.14
  • Accepted : 2020.03.31
  • Published : 2020.04.28

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.

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