[BUIDL Audition Onchain] FS: Vote Analytics Per Audition (Weighted Commentary Insight) #95
Description
Overview
This issue involves building a fullstack analytics interface for each artist’s audition page. The analytics should provide an insightful, real-time view of how each artist is performing based on weighted commentaries, live votes, and judge vs fan engagement.
The design and logic should adapt and expand upon the reference in #57 — Vote Analytics Per Audition Page.
Goals
- Display analytics per audition based on:
- Weighted commentaries (e.g., from judges, fans).
- Vote totals and proportions.
- Commentary count.
- Judge vs fan influence breakdown.
- Visuals should clearly highlight what made an artist successful — not just pitch, confidence, or stage presence, but how their commentary quality and source influenced results.
Frontend Tasks
- Build a UI to show:
- Total number of votes.
- Commentary list (with weights).
- Judge-weighted votes as highlighted or stylized elements.
- Chart/table/visual displaying breakdown of votes.
- Real-time update or refresh when votes/commentaries change.
- Filter options (e.g., by voter type, weight range).
- Use/adapt design guidelines from: #57.
Backend Tasks
- Create endpoints:
GET /api/auditions/:id/vote-analyticsGET /api/auditions/:id/commentary-weight
- Logic to:
- Aggregate votes and classify by type (judge, fan, influencer).
- Calculate weight of each commentary.
- Compute final score as derived from weighted votes.
- Cache or paginate large commentary lists if needed.
Acceptance Criteria
- ✅ Artist’s audition page shows accurate, updated analytics.
- ✅ Commentary weights are reflected visually and in score impact.
- ✅ Voting patterns can be traced by source (judge, fan, influencer).
- ✅ UI matches or improves upon design in issue #57.
Notes
- All commentary should be meaningfully weighted.
- Judges’ votes should show extra visual/functional significance.
- This system is the core evaluation engine behind Musicstrk's audition process.