Digital Sentiment

NARRATIVE & PERCEPTION INTELLIGENCE

// Status: Listening // Protocol: AI SCAN

Continuous scanning of digital conversations to detect emerging narratives, sentiment shifts, and issue traction. This is listening, not polling.

Description

Active

Continuous scanning of digital conversations to detect emerging narratives, sentiment shifts, and issue traction across open and closed ecosystems.

Target: Narrative Velocity

Necessity

  • 01Opinions form digitally before becoming visible.
  • 02Narratives spread faster than surveys can detect.
  • 03Silence in formal data ≠ absence of sentiment.
  • 04Early signals appear as weak, scattered noise.

Components

Multi-platform ingestion
AI-based sentiment detection
Narrative & topic clustering
Velocity & spread analysis
Anomaly & spike detection

Workflow

HOW WE SCAN & ANALYSE

Ingest

Continuous multi-source feeds.
Text, audio, metadata.

Filter

Noise reduction.
Spam & duplication removal.

Analyse

NLP sentiment detection.
Topic & narrative clustering.

Detect

Spike & anomaly detection.
Velocity & spread tracking.

Interpret

Contextual tagging.
Relevance & Impact scoring.

Protocols

QUALITY, BIAS & RELIABILITY CONTROLS

SOURCE VALIDATION

  • Source credibility weighting
  • Bot & coordinated behaviour detection
  • Duplicate source suppression

NOISE CONTROL

  • Volume vs influence differentiation
  • Artificial amplification detection
  • Virality vs relevance separation

CONTEXTUAL ANALYSIS

  • Language & cultural nuance handling
  • Sarcasm & ambiguity safeguards
  • Local context tagging

CROSS-VALIDATION

  • Correlation with CATI trends
  • Field verification where needed
  • Outliers flagged, not exaggerated