딥러닝을 이용한 음악흥행 예측모델 개발 연구
- 콘텐츠랩
- 조회수979
- 2020-11-09
Hyper Link: https://www.koreascience.or.kr/article/JAKO202025465017110.page
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A Study on Development of a Prediction Model for Korean Music Box Office Based on Deep Learning
딥러닝을 이용한 음악흥행 예측모델 개발 연구
- Received : 2020.04.20 Accepted : 2020.07.25 Published : 2020.08.28
Abstract
Among various contents industry, this study especially focused on music industry and tried to develop a prediction model for music box office using deep learning. The deep learning prediction model designed to predict music chart-in period based on 17 variables -singer power, singer influence, featuring singer power, featuring singer influence, number of participating singers, gender of participating singers, lyric writer power, composer power, arranger power, production agency power, distributing agency power, title track, LIKEs on streaming platform, comments on streaming platform, pre-promotion article, teaser-video view, first-week performance. Additionally we conducted a linear regression analysis to sort out factors, and tried to compare the prediction performance between the original DNN prediction model and the DNN model made of sorted out factors.