Journal of Convergence for Information Technology (융합정보논문지)

Convergence Society for SMB (중소기업융합학회)
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Design and implementation of a music recommendation model through social media analytics

소셜 미디어 분석을 통한 음악 추천 모델의 설계 및 구현

  • Chung, Kyoung-Rock (Department of Computer Engineering, Kongju National University) ;
  • Park, Koo-Rack (Department of Computer Science & Engineering, Kongju National University) ;
  • Park, Sang-Hyock (Department of Computer Engineering, Kongju National University)
  • 정경록 (공주대학교 컴퓨터공학과) ;
  • 박구락 (공주대학교 컴퓨터공학과) ;
  • 박상혁 (공주대학교 컴퓨터공학과)
  • Received : 2021.07.31
  • Accepted : 2021.09.20
  • Published : 2021.09.28
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Abstract

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

스마트폰이 빠르게 보급되면서 음악을 생활 속의 배경음악처럼 항상 모든 곳에서 듣는 것이 일반화되어 개인의 상황과 조건에 맞는 추천을 할 수 있는 음악 데이터베이스를 필요하다. 본 논문에서는 소셜 미디어를 통한 음악추천 모델을 제안한다. 소셜 미디어의 데이터를 사용하여 음악 데이터베이스를 작성하고 기존의 음원 제공 플랫폼이 주로 사용하는 협업필터링과는 다른 방식으로 음악을 분류한다. 웹크롤링으로 음악 제목이 해시 태그로 달린 게시글을 찾아 해당 글에 함께 달린 다른 해시 태그들을 수집하고 분류하여 실제 청취자의 음악에 관한 의견을 데이터베이스에 사용한다. 소셜 미디어를 작성할 때의 감정, 상황, 시간대, 날씨 등 많은 조건이 해시 태그에는 포함되어 있으므로 다양한 사람의 의견이 집단지성으로 반영된 소셜 미디어 기반 데이터베이스를 구축할 수 있다.

Keywords

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