How the k-score Works

Each k-score is derived from two primary value dimensions:

1. k₁ — Basic Application Value

Measures a user’s hard value through in-application data such as activity, spending, achievements, and participation.

It is calculated by weighting and normalizing multiple behavioral factors:

k₁ = (Activity Weight × norm(Activity) + Payment Value Weight × norm(Payment Value) + Achievement Weight × norm(Achievement) + Other Dimensions...) /

Σnorm

Activity Metrics — login frequency, task completion, and session duration

Payment Behavior — total historical payments, ARPU, and frequency of purchases

Achievements — levels, badges, progress rates, and special accomplishments

On-Chain Indicators — token trading volumes, NFT holdings, and transaction consistency

more other factors

All sub-dimensions are normalized to a 0–100 scale through min-max processing to ensure comparability and prevent data distortion.

2. k₂ — Social Influence Value

Reflects a user’s soft value — their ability to influence, create, and drive community growth. It follows a similar structure, integrating various social and creative signals:

k₂ = (Social Network Weight × norm(Social Network) + Creator Weight × norm(Creator) + Influence Dissemination Weight × norm(Influence) + On-Chain

Weight × norm(On-Chain) + Other Dimensions...) / Σnorm

Social Network — friend relationships, community activity, and contribution quality Creator Metrics — UGC publication, content quality, and monetization outcomes Influence Spread — sharing reach, user referrals, and engagement propagation Community Participation — involvement in operations, events, or community building more other factors

Both k₁ and k₂ weights are dynamically adjusted using AI and historical performance data, ensuring the system evolves with user behavior and market conditions.

Through this continuous cycle, KapKap transforms digital engagement into an intelligent marketplace of attention — where value flows back to those who create it.