| name | social-sentiment-tracker |
| description | Track and analyze crypto social media sentiment across platforms including Twitter/X, Reddit, Discord, and Telegram to identify narrative shifts, trending topics, and crowd behavior patterns. |
| license | MIT |
| metadata | {"category":"news","difficulty":"intermediate","author":"sperax-team","tags":["news","sentiment","social","twitter","reddit","narratives"]} |
Social Sentiment Tracker
When to use this skill
Use when the user asks about:
- What people are saying about a specific token on social media
- Trending crypto topics or narratives
- Detecting shifts in community sentiment
- Identifying emerging narratives before they go mainstream
- Gauging retail vs informed investor sentiment
Tracking Framework
1. Platform-Specific Analysis
Each platform has different signal quality:
Twitter/X:
- Highest velocity of crypto information
- Key metrics: mention volume, sentiment ratio, engagement rate
- Watch for: influencer threads, developer announcements, project team posts
- Noise factor: High — filter out bots, paid promotions, and engagement farming
Reddit (r/cryptocurrency, r/defi, project-specific subs):
- Longer-form discussion, stronger community signal
- Key metrics: post/comment volume, upvote ratios, daily active commenters
- Watch for: due diligence posts, sentiment shift in comment sections
- Noise factor: Medium — some echo chamber effects
Discord/Telegram:
- Real-time community pulse
- Key metrics: message volume, member growth, moderator activity
- Watch for: team communication frequency and quality, community questions
- Noise factor: High — lots of price speculation and spam
2. Sentiment Scoring
Rate sentiment on a standardized scale:
- Very Bullish (+2): Overwhelming positive discussion, celebration, price target raising
- Bullish (+1): Majority positive, constructive discussion about growth
- Neutral (0): Balanced discussion, no clear direction
- Bearish (-1): Majority negative, concern about fundamentals or price
- Very Bearish (-2): Panic, capitulation language, mass unfollowing
Score each platform independently and create a weighted aggregate.
3. Narrative Detection
Identify and track emerging narratives:
- Current dominant narrative: What theme is driving the most discussion?
- Rising narratives: Topics gaining momentum but not yet mainstream
- Fading narratives: Previously hot topics losing engagement
- Narrative lifecycle: New > Growing > Peak > Declining > Dead
- Narrative examples: "RWA season", "L2 wars", "restaking meta", "AI x crypto"
Track narrative age — narratives that are 2+ weeks old with declining engagement are likely past peak opportunity.
4. Influencer and Smart Follower Analysis
Monitor key opinion leaders:
- Developer accounts: What are core developers building or discussing?
- Analyst accounts: What are respected analysts (not shillers) highlighting?
- Fund/VC accounts: What are institutional participants signaling?
- Contrarian voices: What are known contrarian thinkers saying?
- Credibility weighting: Weight opinions by the source's track record, not follower count
5. Crowd Psychology Indicators
Detect extreme sentiment states:
- FOMO indicators: "Last chance to buy", "never going back to these prices", price target escalation
- Capitulation indicators: "I'm done with crypto", "this time it's different (bearish)", mass unfollowing of crypto accounts
- Complacency indicators: Drop in discussion volume despite high prices — no fear means no hedging
- Denial indicators: Dismissing bearish data, attacking those who raise concerns
6. Contrarian Signals
The crowd is often wrong at extremes:
- When Twitter sentiment is >80% bullish, the top is often near
- When Reddit front page has "crypto is dead" posts, the bottom is often near
- Maximum social volume often coincides with short-term tops
- Minimum social engagement often coincides with the best accumulation opportunities
7. Output Format
- Token/Topic: What was analyzed
- Sentiment score: -2 to +2 with trend direction
- Social volume: High / Normal / Low relative to 30-day average
- Platform breakdown: Twitter / Reddit / Discord sentiment individually
- Dominant narrative: Current driving theme
- Emerging narratives: New themes gaining traction
- Influencer consensus: What key voices are saying
- Crowd psychology state: FOMO / Optimism / Neutral / Fear / Capitulation
- Contrarian signal: What the data suggests the crowd might be wrong about
- Actionable insight: How to use this sentiment information
