Module III: Integrity Layer

Social Reliability & Authenticity

Shield against fraud. Social Reliability Index and Audience Authenticity Score protect your investment from inorganic manipulation.

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Output

What You See

Sample output and dashboard views from this module.

Dashboard: Social Reliability Index (Posting Consistency 3.1-day cadence, Engagement Stability score, Sponsored Ratio); Audience Authenticity (Low Risk Organic vs Bot Network flag); growth trend 2.7%/month. Risk flags visible in Performance Forecasting and Conversion Modeling.

Scenario

Use Case

A concrete scenario where this module delivers value.

Brand manager discovers a creator with high engagement but Integrity Layer flags inorganic spikes. Audience Authenticity Score shows 2.7%/month organic growth vs 40% spike in 2 weeks. She excludes the creator from the campaign - Performance Forecasting and Conversion Modeling never treat the inflated signals as real.

Module III

How It Works

The mechanics that make this module unique.

Social Reliability Index

Posting Consistency, Engagement Stability, Sponsored Ratio - a healthy commercial/organic balance. Unmask inorganic spikes and bought likes.

  • •Posting Consistency - 3.1-day cadence variance
  • •Engagement Stability - unmask inorganic spikes, bought likes
  • •Sponsored Ratio - healthy commercial/organic balance

Audience Authenticity Score

Fraud Detection, Comment Quality, Growth Patterns. Bot networks vs Low Risk Organic. Steady 2.7%/month growth identifies manipulation.

  • •Fraud Detection - bot networks vs Low Risk Organic
  • •Comment Quality - substantive sentiment-rich vs spam
  • •Growth Patterns - steady 2.7%/month to identify manipulation

Risk Flagging for Command Center

Integrity scores flow into every module. Performance Forecasting, Conversion Modeling, and Strategic Guidance down-weight or exclude inorganic sources.

  • •Scores feed Performance Forecasting and Conversion Modeling
  • •Strategic Guidance avoids recommending high-risk creators
  • •Deterministic execution with fraud-aware weighting

Historical Consistency Tracking

Posting and engagement patterns over time. Unmask sudden spikes or bought engagement that distort causal analysis.

  • •Temporal consistency metrics
  • •Anomaly detection for inorganic behavior
  • •Audit trail for compliance and trust

Comment Quality & Sentiment Depth

Substantive vs spam classification. Sentiment-rich comments weighted; empty or bot-like threads down-weighted in Translator and Logic Engine.

  • •Semantic quality from Translator layer
  • •Feeds Psychographic Layer and Strategic Guidance
  • •Protects causal analysis from noise

Command Center

Explore Adjacent Modules

Each module delivers a distinct dimension of intelligence. Continue your journey through the stack.

II. Conversion ModelingIV. Psychographic Layer
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