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Documentation Index

Fetch the complete documentation index at: https://learn.social.plus/llms.txt

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Content Moderation

Build safe and healthy communities with comprehensive moderation tools. Implement content flagging, automated detection, review workflows, and community governance to maintain high-quality discussions.
Looking for a step-by-step walkthrough? The Content Moderation Pipeline guide walks you through building flagging, review, and enforcement flows end-to-end.

Content Flagging

User-driven content reporting with automated and manual review systems

Review Process

Structured workflows for content review, approval, and action management

Auto-Moderation

AI-powered content detection and automated moderation actions

Community Moderation

Establish and enforce clear community standards and policies

Moderation Architecture

Core Moderation Features

  • User Reporting: Easy-to-use reporting interface for community members
  • Multiple Report Types: Spam, harassment, inappropriate content, misinformation
  • Anonymous Reporting: Allow users to report content without revealing identity
  • Bulk Reporting: Handle multiple pieces of content from the same source
  • AI Content Detection: Machine learning models for inappropriate content detection
  • Keyword Filtering: Customizable word filters with context awareness
  • Spam Detection: Pattern recognition for spam and promotional content
  • Image Recognition: Visual content analysis for inappropriate images
  • Moderation Queue: Organized queue system for pending content review
  • Priority Levels: High, medium, low priority handling based on severity
  • Moderator Assignment: Route content to appropriate moderators
  • Review History: Complete audit trail of moderation decisions
  • Content Actions: Hide, remove, edit, or require approval for content
  • User Actions: Warnings, temporary bans, permanent bans, account restrictions
  • Community Actions: Community-wide policy enforcement and announcements
  • Appeal Process: Structured system for users to appeal moderation decisions

Implementation Guide

// Set up basic content flagging
const flaggingConfig = {
  reportTypes: [
    { id: 'spam', label: 'Spam or Promotional Content' },
    { id: 'harassment', label: 'Harassment or Bullying' },
    { id: 'inappropriate', label: 'Inappropriate Content' },
    { id: 'misinformation', label: 'False Information' }
  ],
  anonymousReporting: true,
  autoEscalation: {
    thresholds: {
      spam: 5,
      harassment: 3,
      inappropriate: 2
    }
  }
};

// Enable auto-moderation
const autoModerationConfig = {
  profanityFilter: {
    enabled: true,
    severity: 'medium',
    action: 'flag_for_review'
  },
  spamDetection: {
    enabled: true,
    confidence: 0.8,
    action: 'auto_remove'
  }
};

Moderation Best Practices

  • Clear Policies: Establish clear, understandable community guidelines
  • Consistent Enforcement: Apply rules consistently across all users
  • Transparency: Communicate moderation actions and reasoning clearly
  • Regular Updates: Keep guidelines current with community needs
  • Comprehensive Training: Provide thorough training for all moderators
  • Decision Guidelines: Create clear guidelines for common moderation scenarios
  • Escalation Procedures: Establish when and how to escalate difficult cases
  • Performance Monitoring: Regular review of moderator decisions and performance
  • Human + AI: Combine automated tools with human judgment
  • Context Awareness: Consider context when making moderation decisions
  • False Positive Management: Have processes to handle incorrect automated actions
  • Continuous Improvement: Regularly update and improve moderation systems
  • Quick Response: Respond to reports and appeals promptly
  • Fair Process: Provide fair and transparent appeal processes
  • Educational Approach: Help users understand and follow community guidelines
  • Positive Reinforcement: Recognize and reward positive community behavior