Policy Authoring
Creating effective policies is key to successful content moderation. This section covers best practices specific to the DeepMod platform for writing clear, maintainable policies that balance automation with accuracy.
Quick Reference
Platform Limits:
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Free plans: 25 rules per policy
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Paid plans: 100 rules per policy
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Rule names: 5-80 characters
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Rule content: 5-160 characters
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Webhook configured at organization level for production use
Policy Structure
Start with Clear Organization
Policy Naming: Use descriptive names that reflect the policy's purpose, like "Community Guidelines" or "Product Review Standards." Each policy gets a unique friendly identifier (like "community-guidelines") for API usage.
Rule Groups: Organize rules into logical categories:
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Safety: User protection, harassment, harmful content
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Legal: Compliance, copyright, privacy, regulatory requirements
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Brand: Brand standards, messaging guidelines, competitor mentions
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Spam: Promotional content, repetitive posts, unwanted links
This organization makes policies easier to understand, manage, and tune over time.
Rule Limits and Planning
Rule Limits:
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Free plans: 25 rules per policy
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Paid plans: 100 rules per policy
Start Small: Begin with 5-10 high-impact rules covering your most critical content issues. You can always add more rules as you learn how the system performs with your content.
Writing Effective Rules
Rule Names: Keep names concise but descriptive (5-80 characters)
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Good: "Personal Information Disclosure"
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Avoid: "PII" or "Must not contain any personally identifiable information including but not limited to..."
Rule Content: Be specific and clear (5-160 characters)
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Good: "text containing phone numbers, email addresses, or home addresses"
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Good: "content promoting violence or illegal drug sales"
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Avoid: "personal information" (too vague) or "bad content" (too broad)
Using Rule Presets
DeepMod provides pre-written rule templates to help you get started quickly:
Available Presets: Financial information, personal data, HIPAA violations, and other common content categories
When to Use Presets:
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Starting a new policy in a familiar domain
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Adding standard compliance rules
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Learning effective rule-writing patterns
Customization: You can modify preset content to match your specific needs after adding them to your policy.
Configuration Best Practices
Confidence Thresholds
Start Conservative: Begin with 75-80% confidence threshold
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Reduces false positives while you learn system behavior
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Easier to lower threshold later than deal with user complaints
Adjust Based on Results:
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Too many false positives? Increase threshold
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Missing obvious violations? Decrease threshold
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High ambiguous rate? Consider if human review is needed
Review Mode Selection
No Review Mode: Choose when:
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You can tolerate some false negatives
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Content volume is high
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Processing speed is priority
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You don't have review team capacity
Human Review Mode: Choose when:
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Accuracy is critical
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Content decisions have significant consequences
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You have trained reviewers available
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Regulatory compliance requires human oversight
Common Patterns and Anti-Patterns
Effective Rule Patterns
Specific Content Types:
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"text containing credit card numbers or banking information"
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"content promoting illegal drug sales or usage"
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"messages containing threats of physical violence"
Brand Guidelines:
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"content mentioning competitor brand names"
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"text using inappropriate language for customer communications"
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"promotional content without proper disclaimers"
Anti-Patterns to Avoid
Overly Broad Rules:
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Avoid: "negative content" (too vague)
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Better: "content expressing hostility toward specific individuals"
Conflicting Rules:
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Don't create rules that contradict each other
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Example: One rule allowing "educational content about sensitive topics" while another blocks "any mention of sensitive topics"
Context-Insensitive Rules:
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Consider how legitimate content might trigger your rules
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Educational, news, and creative content often discusses sensitive topics appropriately
Testing and Iteration
Policy Testing
Use Test Mode: Always test new policies and rule changes before activating
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Test with representative content samples
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Check for unexpected false positives
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Verify confidence scores align with expectations
Gradual Rollout:
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Test with small content samples
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Review results and adjust rules/thresholds
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Activate for live content monitoring
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Monitor initial results closely
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Fine-tune based on real-world performance
Ongoing Optimization
Regular Review: Monthly assessment of policy performance
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Check false positive/negative rates
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Review ambiguous case patterns
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Analyze which rules trigger most frequently
Rule Refinement:
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Merge similar rules that always trigger together
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Split overly broad rules that catch too much benign content
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Remove rules that never trigger or add no value
Documentation: Keep notes on why rules were added and any modifications made. This helps with future maintenance and team handoffs.
Webhook Integration
Webhook Configuration: Configure your organization webhook in Organization Settings to receive all moderation results.
Webhook Testing: Verify your webhook endpoint before activating policies:
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Confirms your system can receive results
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Validates response format handling
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Tests error handling for failed deliveries
Result Handling
Plan for All Result Types: Ensure your webhook handler processes Success, Failure, and Ambiguous results appropriately
Metadata Usage: Include relevant metadata with moderation requests to help with content routing and analytics
Scaling Considerations
Multiple Policies
Policy Separation: Create separate policies for different content types or risk levels:
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User-generated content vs. customer support messages
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Public content vs. internal communications
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Different geographic regions with varying standards
Shared Learning: Apply lessons learned from one policy to improve others
Team Collaboration
Clear Ownership: Assign responsibility for policy maintenance and updates
Change Management: Establish processes for:
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Requesting policy changes
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Testing and approving modifications
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Communicating updates to relevant teams
What's Next
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Plan Usage & Limits - Monitor policy usage and manage plan limits
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Interpreting Results - Analyze policy performance and optimize based on results
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Human Review Workflows - Set up human oversight for ambiguous cases
Effective policy authoring is an iterative process. Start simple, test thoroughly, and refine based on real-world performance to build robust content moderation that serves your specific needs.
Need help with policy design? Contact our support team for guidance on rule writing, threshold tuning, and policy optimization strategies.