Algorithmic Model

The TasteScore engine is powered by a multi-factor algorithm that synthesizes:

• Behavioral input signals (e.g., voting history, engagement velocity)

• Social graph analytics (e.g., interactions with high-TasteScore accounts)

• Contextual content evaluation (e.g., fashion quality, uniqueness, remix lineage)

• AI feedback loops (e.g., generative AI interpreting style coherence or sentiment)

TasteScore is calculated using a weighted composite model:

TasteScore = f(Engagement * Style Quality * Social Trust * Influence Spread)

Each variable is adjusted in real-time via machine learning models that ingest on-chain events, AI-enhanced metadata, and cross-account interaction patterns.