| Summary: | 碩士 === 國立交通大學 === 科技管理研究所 === 105 === Music is an indispensable thing in our lives. With the advances in technology, we can play the music whenever we want than before.
Users of music streaming services grow larger day by day. However, a gap between the advances recommender system of music streaming services and the user experience. Recently, user research of music field discovered some phenomenon. Ward, Goodman, and Irwin proved that familiarity is an important factor when people make music choice(2014). Moreover, researchers tend to use API to collect data and explains user's behavior in the music field, temporal dynamics also proved an important factor as well.
In this study, mixed methods were used to develop personas from 53 users recruited from Facebook and BBS, all of them use Spotify to listen to music mainly. After getting authentication from all the participants, their listening data had been collected from 2017/3/28 to 2017/4/18 through Spotify Web API. Principle Component Analysis and Cluster analysis was used to separate users to the different group, then representative users were selected for in-depth interview to gain insights for each cluster.
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