Using personalized radio to enhance local music discovery

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Conference Proceeding

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We explore the use of personalized radio to facilitate the discovery of music created by local artists. We describe a system called MegsRadio.fm that produces a customizable stream of music by both local and well-known (non-local) artists based on seed artists, tags, venues and/or location. We hypothesize that the more popular artists provide context for introducing new music by more obscure local artists. We also suggest that both the easy-to-use and serendipitous nature of the radio model are advantageous when designing a system to help individuals discover new music. Finally, we describe an interactive map that features personalized event recommendations based on the user's listening history. Results from a small-scale user study indicate that users are more aware of the local music scene after using it, discover relevant local music events, and would recommend the experience to others.

Publication Name

Conference on Human Factors in Computing Systems - Proceedings

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