Predicting Performance on Media Service: Analyzing Music Video Data on YouTube
| Autor: | Lung-Hsiung Chen, 陳隆翔 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 In recent years, the habits of watching media in Taiwan have been changing, media platforms such as YouTube have become an important platform for people to get entertainment and information. The profits of the physical musice recording industry have gradually declined, while the profits of digital music have increased year by year and even the streaming services have experienced a signicicant growth. At present, many music media companies will choose to upload MV (Music Video) to YouTube when the song recordings are released, so that viewers can experience the best viewing quality, that is, the dual experience of visual and audio, and thus become a potential motivation for their further experience with the music or singer. With the prevalence of streaming media platform, achieving a successful user experience on the audio-visual platform and converting it into a revenue-generating download is an important indicator of song performance for music companies, and YouTube is the easiest way for listener to have first interaction with the music or singer. Our study researcher on YouTube''s official music video data, attempting to predict streaming traffic volume on Spotify, and to figure out which factors may be relevant to this conversion. In the future, relevant personnel can conduct a further research into it and conduct their decision on marketing strategy based on our results. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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