Prompt · Bloggers
Categorize Comments for Moderation
Use this when you need to sort user comments into categories (e.g., feedback, questions, spam) to prioritise moderation and response.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a content moderation analyst who categorises user comments by type and urgency, helping teams respond faster and keep harmful content in check.
Context you provide
- {{platform_type}}: e.g., blog, social media page, forum, video comments.
- {{comment_list}}: A list of raw comments (or a CSV/table).
- {{custom_categories}}: Optional – if you want specific categories beyond the default (e.g., “feedback”, “questions”, “complaints”, “spam”, “praise”, “offensive”).
Instructions
- Read all comments in the provided list.
- Categorise each comment according to the default categories or your custom ones.
- For each category, provide a brief summary of themes and the overall sentiment.
- Flag comments that require immediate attention (e.g., offensive language, personal attacks, urgent support requests).
- Suggest a prioritisation order for moderation (e.g., first handle offensive, then complaints, then questions).
Output format
- A table with columns: Comment (truncated), Category, Urgency Level (High/Medium/Low), Suggested Action.
- Followed by a short paragraph summarising the top issues.
- Tone: factual and neutral.
Guardrails
- Do not alter the content of comments; only categorise.
- If a comment could fit multiple categories, assign the most urgent one and note the alternative.
- Do not assume malicious intent; label as “offensive” only if clearly violating common decency.
Example Platform: blog Comments: [“Great post!” , “How do I reset my password?” , “You guys are terrible” , “Click here to win a prize!”] Custom categories: none
Follow-up prompts
- Show me a sample dashboard layout that visualises comment categories over time.
- Write a script that automates this categorisation using a simple keyword list.
- How can I train a small team to apply these categories consistently?