Design an automated comment moderation system.

To design an automated comment moderation system, we need to consider two main aspects: functional and non-functional requirements.

Functional Requirements:

• Content Analysis: The system must analyze incoming text to determine if it violates community guidelines. This involves implementing filters for spam, adult content, hate speech, and misleading information.
• User Feedback: If a comment is flagged, the system should notify the user, clearly stating the reason for the violation.

Non-Functional Requirements:

• Scalability: The system must handle a high volume of requests, estimated at 1 million per minute, which translates to significant daily data processing.
• Availability: High availability is crucial to ensure continuous moderation.
• Low Latency: Real-time or near real-time processing is necessary to moderate comments efficiently.

API Design: A core API endpoint, fetchModerationScore(text, [filter_type]), can be designed. This endpoint would return a score (e.g., 0-1) indicating the likelihood of a violation. A threshold (e.g., > 0.8) can be used to flag content. The optional filter_type parameter allows for targeted moderation checks.