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The PartyVote Music Library Visualization System

The Party Vote Music Library Visualization System enables seamless music collaboration among closely knit social groups, creating a dynamic experience without playlists or DJs. Designed for 10-20 participants, the system features over 500 songs, ensuring 6 hours of non-repeating music. Participants vote for songs, albums, or artists, adjusting their weights to cluster similar songs for optimal playback. This lightweight and user-friendly interface encourages engagement and enhances group understanding of music preferences while addressing challenges such as clustering algorithms and coding complexities.

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The PartyVote Music Library Visualization System

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  1. The PartyVote Music Library Visualization System No play list, no DJ, no problem! Nadia Rashid, David Sprague, and Fuqu Wu

  2. Motivation

  3. Previous Literature • Jukola • Pandora • MUSICtable

  4. Visualization Goals • Co-present music collaboration for closely knit social groups • Lightweight • Enable system understanding • Optimal for participants

  5. System Usage • 10-20 participants • 500+ songs • 6 hours of non-repeating music.

  6. General Overview

  7. Voting & Music Selection • All songs start with weighting of 0 • Participants vote for a song/album or artist • Weight = Weight + (1/# of songs) • Similar songs also affected by votes. • High dimensional cluster/hull defined by songs with weight > 0 • Songs in this cluster are potentially played.

  8. Vote Clustering

  9. Vote Clustering

  10. Vote Clustering

  11. The Interface

  12. Interface part 2

  13. Challenges • MDS and Convex Hull/Clustering Algorithm. • Lots and LOTS of coding • Evaluation and distance metric tweaking

  14. Visualization Goals Revisited • Co-present music collaboration for closely knit social groups ✔ • Lightweight ✔ • Enable system understanding ✔ • Optimal for participants ✔

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