Ban Topics Agent

The Ban Topics Agent prevents discussions on specific subject areas by identifying and filtering content that relates to prohibited topics. It helps maintain content policies, enforce community guidelines, and avoid discussions in sensitive or off-topic subject areas.

Ban Topics Agent interface and configuration

Usage Notice: Configure topic detection with care to avoid overly restricting legitimate discussions. Topic ban systems work best when focused on clearly defined subject areas rather than broad conceptual categories.

Component Inputs

Input Text: The text content to be analyzed for banned topics
Example: "Let's discuss cryptocurrency investment strategies and which coins to buy."
Banned Topics: List of topics that should trigger content filtering
Example: "cryptocurrency,gambling,illegal_activities,adult_content"
Threshold: Sensitivity level for topic detection
Range: 0.0 to 1.0 (default: 0.6)
Lower values increase detection sensitivity but may trigger more false positives
Is Blocked: Whether content with banned topics should be blocked
Options: true (block content) or false (allow but flag content)

Component Outputs

Safety Status: Overall assessment of topic detection results
Values: Safe (no banned topics), Unsafe (banned topics detected)
Risk Score: Numerical evaluation of policy violation risk
Scale: 0.0 (no risk) to 1.0 (high risk)
Detected Topics: List of identified banned topics in the content
Example: ["cryptocurrency"]
Topic Matches: Detailed information about each detected topic
Includes confidence scores and relevant text segments

Common Banned Topic Categories

Content Policy Categories

Adult/NSFW Content
Illegal Activities
Hate Speech Subjects
Violence & Weapons
Harmful Substances
Gambling & Betting

Specialized Categories

Financial Advice
Medical Guidance
Political Discussions
Religious Topics
Competitor Products
Off-Topic Subjects

How It Works

The Ban Topics Agent uses semantic understanding of content to identify prohibited subject areas. Rather than simple keyword matching, it analyzes the context, meaning, and subject matter of text to determine if it relates to any of the configured banned topics.

Detection Techniques

Semantic topic modeling to understand content themes
Named entity recognition to identify subject-specific terms
Contextual analysis to understand discussion intent
Knowledge graph integration for topic relationship mapping
Classification models trained on topic-specific content

Use Cases

Content Moderation: Enforce community guidelines on forums and social platforms
Educational Environments: Keep discussions focused on curriculum-appropriate topics
Customer Support: Prevent discussions about services not offered by your company
Professional Communities: Maintain on-topic discussions in specialized platforms
Legal Compliance: Avoid regulated topics that require specialized licensing

Implementation Example

const topicFilter = new BanTopicsAgent({
  bannedTopics: ["cryptocurrency", "gambling", "medical_advice"],
  threshold: 0.7,
  isBlocked: true
});

const inputText = "What do you think about investing in Bitcoin";
const result = topicFilter.analyze(inputText);

// Output:
// {
//   safetyStatus: "Unsafe",
//   riskScore: 0.86,
//   detectedTopics: ["cryptocurrency"],
//   topicMatches: [
//     {
//       topic: "cryptocurrency",
//       confidence: 0.92,
//       segments: ["Bitcoin", "Ethereum", "investing"],
//       explanation: "Content discusses cryptocurrency investment advice"
//     }
//   ]
// }

Useful Resources

Best Practices

Define banned topics with specific, clear boundaries to avoid ambiguity
Consider cultural and contextual factors when configuring topic restrictions
Regularly review and update banned topic definitions based on emerging trends
Implement feedback mechanisms to improve topic detection accuracy over time
Use transparent messaging to explain why certain topics are prohibited

Documentation