Sentiment Analyzer

When to activate

Daily (automated alert-driven). Before/after major announcements. When engagement metrics shift. Input: member posts, comments, reactions, moderation reports. Output: sentiment score (0–100), trend, alerts, topic tags.

When NOT to use

Not to shadowban members based on sentiment score. Not as a substitute for human judgment. Not to assume correlation without context.

Sentiment Analysis Checklist

Execute in order:

1. Gather sentiment signals — Collect: positive reactions (likes, thumbs up), negative reactions (angry, sad), comment tone (positive/neutral/negative), moderation reports, member feedback
2. Calculate sentiment baseline — For past week: % positive reactions, % negative reactions, % neutral. Compare to prior week and prior month.
3. Identify emerging frustrations — Are certain topics appearing in multiple removal reports? Are specific features getting criticism? Are moderation decisions creating backlash?
4. Tag trending topics — What are members talking most about? Categorize: Product feedback, Feature request, Celebration, Complaint, Question, Discussion.
5. Measure reply positivity ratio — When members reply to posts, is tone constructive or dismissive? Are debates healthy or turning heated?
6. Score conversation health — 0–100 scale: positive_ratio (40%) + constructive_tone (30%) + psychological_safety (20%) + respect (10%)
7. Detect crisis signals — Watch for: misinformation spreading, harassment campaigns, privacy concerns, safety threats, member exit announcements
8. Segment by channel/member type — Does sentiment vary by channel? Do power users feel differently than new members?
9. Generate alerts — If sentiment drops >15%, engagement sentiment turns negative, or crisis signals detected, flag for immediate review
10. Log trends — Track sentiment trajectory weekly. Is community becoming more positive, neutral, or negative?

Sentiment Scoring Framework

Score = (Positive weight × 100) - (Negative weight × 100)

Weekly Sentiment Report Template

# Community Sentiment Report — Week of [DATE]

**Overall Sentiment Score:** 72/100 — [Status: Positive / Neutral / Negative]
**Trend:** [Stable / Improving / Declining] (compare to prior week)

---

## Sentiment Breakdown

| Signal | This Week | Last Week | Change |
|---|---|---|---|
| Positive reactions | 68% | 70% | -2% |
| Negative reactions | 8% | 6% | +2% |
| Neutral reactions | 24% | 24% | — |
| Constructive tone | 85% | 87% | -2% |
| Psychological safety score | 76/100 | 78/100 | -2 |

---

## Top Trending Topics (This Week)

| Topic | Mentions | Sentiment | Status |
|---|---|---|---|
| Feature X launch | 32 | 81% positive | Celebration |
| Bug report: Y | 18 | 45% negative | Concern |
| Career advice thread | 24 | 92% positive | Healthy discussion |
| Moderation decision Z | 12 | 35% negative | Frustration |

---

## Emerging Frustrations

- **Moderation perception:** 2 members report feeling unfairly treated in [decision Z]. Consider transparency post or appeal review.
- **Feature parity concern:** 4+ members asking when [feature] lands on [platform]. Clarity needed from product team.
- **Onboarding friction:** New members asking "how do I X" repeatedly; FAQ section may be unclear.

---

## Celebration Moments

- [Power user name] celebrated promotion — 28 reactions, heartfelt responses.
- [Member] shared win on [achievement] — 35 reactions, inspired others to share wins too.

---

## Alerts (Requiring Action)

- Sentiment on [topic] dropped 24% this week. Monitor for escalation.
- 3 removal reports for same member type of offense; moderation consistency check needed.
- Misinformation thread on [topic] — 6 upvotes before removal. Fact-check effort underway.

---

## Channel Health Snapshot

| Channel | Sentiment Score | Trend | Primary Vibe |
|---|---|---|---|
| #general | 74 | Stable | Helpful, collaborative |
| #help | 71 | Stable | Supportive, solution-focused |
| #announcements | 68 | Declining | Mixed excitement + concerns |
| #introductions | 85 | Improving | Welcoming, encouraging |

---

## Recommendations

1. **Boost #announcements sentiment:** Pair feature announcements with known benefits for end users. Include feedback loop ("What would help you use this?").
2. **Clarify feature roadmap:** Product team to post ETA on [feature] by [date]. Reduces speculation.
3. **Review moderation transparency:** Post decision log weekly. Shows consistency, builds trust.

Crisis Signal Checklist

Monitor for:

• Misinformation spike: Same false claim in 3+ threads. Fact-check immediately.
• Harassment campaign: 2+ coordinated negative comments directed at 1 member or group.
• Privacy breach signal: Members mentioning leaked data, screenshots of private info, or account compromise.
• Safety threat: Any mention of violence, self-harm, threats, or illegal activity. Escalate to legal/safety immediately.
• Mass member exit: 5+ members posting "I'm leaving because..." in short timeframe.
• Toxic tone shift: Language becomes hostile, respectful debate turns into personal attacks, psychological safety drops >20 points.