# Moderation System Overview

## Purpose
The moderation system ensures high-quality, accurate content across the ThrillWiki platform by implementing a structured review process for user-generated content.

## Core Components

### 1. Content Queue Management
- Submission categorization
- Priority assignment
- Review distribution
- Queue monitoring

### 2. Review Process
- Multi-step verification
- Content validation rules
- Media review workflow
- Quality metrics

### 3. Moderator Tools
- Review interface
- Action tracking
- Decision history
- Performance metrics

## Implementation

### Models
```python
# Key models in moderation/models.py
- ModeratedContent
- ModeratorAction
- ContentQueue
- QualityMetric
```

### Workflows

1. Content Submission
   - Content validation
   - Automated checks
   - Queue assignment
   - Submitter notification

2. Review Process
   - Moderator assignment
   - Content evaluation
   - Decision making
   - Action recording

3. Quality Control
   - Metric tracking
   - Performance monitoring
   - Accuracy assessment
   - Review auditing

## Integration Points

### 1. User System
- Submission tracking
- Status notifications
- User reputation
- Appeal process

### 2. Content Systems
- Parks content
- Ride information
- Review system
- Media handling

### 3. Analytics
- Quality metrics
- Processing times
- Accuracy rates
- User satisfaction

## Business Rules

### Content Standards
1. Accuracy Requirements
   - Factual verification
   - Source validation
   - Update frequency
   - Completeness checks

2. Quality Guidelines
   - Writing standards
   - Media requirements
   - Information depth
   - Format compliance

### Moderation Rules
1. Review Criteria
   - Content accuracy
   - Quality standards
   - Community guidelines
   - Legal compliance

2. Action Framework
   - Approval process
   - Rejection handling
   - Revision requests
   - Appeals management

## Future Enhancements

### Planned Improvements
1. Short-term
   - Enhanced automation
   - Improved metrics
   - UI refinements
   - Performance optimization

2. Long-term
   - AI assistance
   - Advanced analytics
   - Workflow automation
   - Community integration

### Integration Opportunities
1. Machine Learning
   - Content classification
   - Quality prediction
   - Spam detection
   - Priority assignment

2. Community Features
   - Trusted reviewers
   - Expert validation
   - Community flags
   - Reputation system