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Structuring a Resource-Aware Content & Feedback Engine

· 2 min read
samundrak
JavaScript Dev

Overview​

Once data is live, platforms become conversations. In this post, I’ll explain how I created a resource-aware content and feedback engine where users can:

  • Read and write multilingual content
  • Rate political entities (parties, leaders, governments)
  • Comment on historical events and scandals
  • Attach feedback directly to any model in the system

The system is powered by polymorphic content linking, a unified comment engine, and approval metrics.

Design Goals​

  • ✅ Support comments, ratings, reactions, and editorial content
  • ✅ Link all feedback and content to any resource (party, leader, election, etc.)
  • ✅ Make everything bilingual
  • ✅ Avoid duplicating logic across models

This meant creating a generalized system that could scale both horizontally (new content types) and vertically (across domain models).

Core Schema (Prisma)​

Here’s the core structure I used:

model Content {
  id           Int      @id @default(autoincrement())
  resourceType String   // e.g., 'LEADER', 'PARTY', 'ELECTION'
  resourceId   Int
  contentType  String   // COMMENT, SCANDAL, RATING, EDITORIAL
  contentStatus String  // APPROVED, FLAGGED, DELETED
  title        String?
  titleLocal   String?
  content      String
  contentLocal String?
  eventDate    DateTime?
  parentContentId Int?
  createdAt    DateTime @default(now())
}

This lets a single table support:

  • Comments and replies (via parentContentId)
  • Ratings and feedback
  • Multi-level editorial content

Ratings & Approval Metrics​

Ratings are a special type of content with structure:

{
  resourceType: 'PARTY',
  resourceId: 25,
  contentType: 'RATING',
  content: '4',
  contentLocal: '४',
}

Aggregations are done on the backend to compute:

  • Average rating per resource
  • Most-rated items by category
  • Rating trends over time (coming soon)

User Experience​

On the frontend, I use a shared component:

<ResourceFeedback resourceType="LEADER" resourceId={id} />

This internally loads and renders:

  • Ratings bar
  • Add comment box
  • Comment thread with moderation tools

Content Moderation​

Admins can flag content with statuses (APPROVED, FLAGGED, DELETED) and hide inappropriate or spam entries. These statuses also allow:

  • Public visibility filtering
  • Analytics around abuse patterns

Future: Add moderation dashboards and approval workflows.

Bilingual Content Support​

Every content entry supports both English and Nepali. UI falls back gracefully, and users can toggle languages in their preferences or URL path.

Conclusion​

Creating a polymorphic content engine let me scale feedback and editorial contributions across every part of the civic dataset.

The same structure powers:

  • Scandal logs
  • User comments
  • Leader approval tracking
  • Party ratings
  • Threaded debates

Next up: I’ll dive into how I modeled political scandal timelines and encoded hierarchy, sources, and localization into structured records.