Comment Mining

Overview

When to Use

• analyze comments on a TikTok, YouTube video, Instagram Reel, Facebook post, Reddit post, or Rumble video
• find audience questions, objections, complaints, or buying intent
• extract voice-of-customer language
• find content ideas from comments
• understand sentiment around a post, creator, product, or topic

Comment Sources

/v1/tiktok/video/comments

/v1/tiktok/video/comment/replies

/v1/youtube/video/comments

/v1/youtube/video/comment/replies

/v2/instagram/post/comments

/v1/facebook/post/comments

/v1/facebook/post/comment/replies

/v1/reddit/post/comments

/v1/rumble/video/comments

Workflow

1. Fetch comments
   • Use the post/video URL whenever possible.
   • Paginate when the endpoint supports it and the user wants depth.
   • Preserve comment text, author if public, like/upvote count, timestamp, and source URL.
2. Clean lightly
   • Remove obvious spam/duplicates.
   • Keep slang, misspellings, and emotional wording if it is useful customer language.
   • Do not over-normalize exact quotes.
3. Classify each useful comment Use these buckets:
   • questions
   • objections
   • complaints/pain points
   • praise
   • confusion
   • requests/feature ideas
   • buying intent
   • controversy/debate
   • jokes/memes/culture signals
4. Cluster themes
   • Group similar comments.
   • Score themes by frequency and intensity.
   • Highlight exact quotes for each theme.
5. Turn insights into actions Depending on the user's goal, produce:
   • content ideas
   • FAQ ideas
   • landing page copy angles
   • product ideas
   • objection-handling bullets
   • sales/support notes

Output Format

# Comment Mining Report

## Summary
- Source(s): {urls}
- Comments analyzed: {count}
- Confidence: High/Medium/Low

## Top Themes
| Theme | Type | Frequency | Intensity | Representative quote |
|---|---|---:|---|---|

## Audience Questions
- "..."

## Objections and Concerns
- **Objection:** ...
  - Evidence: "..."
  - Response angle: ...

## Buying Intent / Demand Signals
- "..."

## Exact Language to Reuse
- "..."
- "..."

## Content Ideas From Comments
1. ...
2. ...

Quality Guardrails

• Label sample size and confidence.
• Separate one loud comment from a repeated pattern.
• Preserve exact quotes for useful language.
• Avoid claiming broad market sentiment from one post's comments.
• Call out moderation/platform bias when relevant.

Common Pitfalls

• Do not flatten comments into generic sentiment. The value is in questions, objections, and exact wording.
• Do not include personally identifying details unless they are already public and necessary.
• Do not treat bot/spam comments as audience signal.
• Do not skip Reddit post context. For Reddit, read both the original post and comments.