comment-mining
Use when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.
git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills /tmp/comment-mining && cp -r /tmp/comment-mining/skills/comment-mining ~/.claude/skills/comment-miningSKILL.md
# Comment Mining
## Overview
Mine public comments for what people actually ask, complain about, want, misunderstand, or repeat. The output should help with product research, content ideas, copywriting, objection handling, and audience understanding.
## When to Use
Use this skill when the user asks to:
- 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
| Platform | Endpoint |
|---|---|
| TikTok comments | `/v1/tiktok/video/comments` |
| TikTok replies | `/v1/tiktok/video/comment/replies` |
| YouTube comments | `/v1/youtube/video/comments` |
| YouTube replies | `/v1/youtube/video/comment/replies` |
| Instagram comments | `/v2/instagram/post/comments` |
| Facebook comments | `/v1/facebook/post/comments` |
| Facebook replies | `/v1/facebook/post/comment/replies` |
| Reddit comments | `/v1/reddit/post/comments` |
| Rumble 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
```markdown
# 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.Use when the user wants to analyze active ads from Meta/Facebook, Google, or LinkedIn ad libraries; tear down a competitor's messaging; extract hooks, offers, CTAs, video transcripts, landing page claims, and test ideas from public ads.
Use when the user wants to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following data, comments, geography, language, and content fit. Helps judge sponsorship and market fit.
Use when the user wants to research competitors' social media strategy, compare brands or creators, find what content is working in a niche, identify content gaps, or produce a practical social strategy brief from public social data.
Use when the user wants to turn public social videos, transcripts, posts, or creator research into reusable content assets such as LinkedIn posts, X threads, short-form scripts, newsletters, blog outlines, carousels, or content calendars.
Use when the user wants to analyze a creator, influencer, founder, or brand social account and understand positioning, content pillars, outlier posts, hooks, format choices, audience reaction, and what can be copied or tested.
Use when the user wants to find creators, influencers, affiliates, or social accounts in a niche for outreach, partnerships, sponsorships, UGC, seeding, or competitive research. Produces scored prospect lists from public social data.
Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.
Use when the user wants to validate a product idea, find pain points, mine demand signals, discover objections, or gather voice-of-customer language from Reddit, social posts, video transcripts, and comments. Produces evidence-backed product research.