Emotion & Rumor Analysis
MP7-003 Buzz Tracking, MP7-004 Emotion Analysis & Rumor Management
MP7-003: Buzz Tracking & Velocity Analysis
Real-time monitoring with 3,450+ keyword taxonomy
Keyword Taxonomy
- Policy (840)
- Leadership (620)
- Issue-based (1,100)
- Anti-corruption (450)
- Regional (440)
Top 5 Monitoring Keywords
Velocity Alert Levels
MP7-004: Emotion Analysis & Segment-Wise Tracking
Affective dimension analysis - emotions driving voter behavior
Primary Emotion Drivers
Anger
Very High (85%)Triggers: Broken promises, Drug crisis, Unemployment, SYL canal
Actionable: Yes - channel into policy critique
Fear
High (72%)Triggers: Security, Religious harmony, Economic stability, Job loss
Actionable: Yes - security narrative
Betrayal
Very High (81%)Triggers: Candidate defection, Broken commitments, Leadership vacuum
Actionable: Yes - trust rebuilding
Resignation
Moderate (58%)Triggers: Youth emigration, Political disillusionment, Cynicism
Actionable: Difficult - hope messaging required
Hope
Moderate (52%)Triggers: New leadership, Policy promises, Change narrative
Actionable: Yes - amplify aspirational
Pride
High (76%)Triggers: Sikh pride, Punjabi language, Agricultural heritage, Cultural identity
Actionable: Yes - heritage celebration
Segment-Wise Emotion Analysis
| Voter Segment | Primary Emotion | Intensity | Shift Direction |
|---|---|---|---|
| Urban Youth (18-25) | Anger + Resignation | Very High | AAP-Congress or NOTA |
| Rural Youth (18-35) | Anger + Betrayal | High | AAP-Congress (drug crisis) |
| Women (All) | Frustration + Hope | High | AAP loyal but disappointed |
| SC Voters | Betrayal + Anger | Very High | AAP-Congress (Mazhabi) |
| Jat Farmers | Anger + Resignation | High | SAD/BJP or Congress |
| Urban Middle Class | Cynicism + Betrayal | High | AAP-BJP or Congress |
| NRI Community | Anger + Pride | Very High | Pro-Congress (historical) |
MP7-004: Rumor Management Framework
Detection - Verification - Response - Containment
Response Time Targets
<45 min
Detection - Alert
<2 hrs
Alert - Verification
<4 hrs
Verification - Response
>85%
Containment Target (Tier 2)
Response Playbook
Detect
Social listening + keyword alerts
SLA: <15 min
Verify
Fact-check team + ground truth
SLA: <2 hrs
Amplify
Pre-bunking content + influencer network
SLA: <4 hrs
Contain
Counter-narrative + official response
SLA: <8 hrs
Learn
Post-incident analysis + update playbook
SLA: 24 hrs
Known Rumor Scenarios (Priority Pre-Bunk)
| Rumor | Risk | Probability | Mitigation |
|---|---|---|---|
| Congress is Anti-Sikh | CRITICAL | 85% | Historical record, 1984 context, comparative |
| Congress Sold Out Farmers | HIGH | 70% | MSP in writing, farm laws opposition record |
| All Parties Same / Nothing Changes | HIGH | 75% | Concrete deliverables, specific commitments |
| Congress Can't Win / Strategic Voting | HIGH | 80% | Internal polling data, voter contact evidence |
| Congress Leaders Are Corrupt | MODERATE | 60% | Reform documentation, accountability frameworks |
CRITICAL:"Congress is Anti-Sikh" narrative requires immediate pre-bunking. Probability 85%, Impact Severe. Historical record + 1984 context + comparative framing required before narrative gains traction.
Sentiment Velocity Thresholds (B18 Methodology)
Monitoring benchmarks for social media virality
| Velocity Level | Threshold | Alert Status |
|---|---|---|
| Low | <10 mentions/hour | Normal monitoring |
| Rising | 10-50 mentions/hour | Watch |
| High | 50-200 mentions/hour | Active tracking |
| Viral | >200 mentions/hour | Crisis protocol |
Pre-Bunking Categories (G32 Framework)
Pre-bunking is cheaper than reactive response - build resistance before rumor circulates
Historical Record
Green Revolution, 1984, minority empowerment
Policy Position
SYL canal, MSP guarantee, drug plan
Comparative
AAP delivery vs Congress, SAD betrayal
Vulnerability
Why Congress lost 2022, leadership renewal