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nara

Clout

Clout is a subjective measure of a nara’s reputation and social standing, derived from its interactions and the “resonance” those interactions have with others.

1. Purpose

Section titled “1. Purpose”
  • Provide a decentralized mechanism for ranking naras based on their activity and social impact.
  • Help naras prioritize information (gossip, sync) from “important” or “interesting” peers.
  • Reward stability, uptime, and meaningful social participation.

2. Conceptual Model

Section titled “2. Conceptual Model”
  • Clout Score: A numerical value representing reputation.
  • Resonance: A multiplier derived from how much an interaction matches a nara’s personality.
  • Interactions: Events like teasing, seen proofs, and presence announcements that contribute to clout.
  • Decay: Clout is not permanent; old interactions lose influence over time.

Invariants

Section titled “Invariants”
  1. Subjectivity: Every nara calculates Clout differently based on its own personality.
  2. Event-Sourced: Clout MUST be entirely derived from the event ledger.
  3. No Central Authority: There is no global “High Score”; rankings only exist in the mind of the observer.

3. External Behavior

Section titled “3. External Behavior”
  • naras use Clout scores to decide which peers to sync with first or whose gossip to prioritize.
  • The Web UI displays Clout rankings to show which naras are currently “resonant” in the neighborhood.
  • High Clout scores may influence social interactions (e.g., naras are more likely to tease high-clout peers).

4. Interfaces

Section titled “4. Interfaces”
  • CloutProjection: The read-model responsible for computing scores from the ledger.
  • GetClout(naraID): Retrieves the current subjective score for a peer.

5. Event Types & Schemas

Section titled “5. Event Types & Schemas”

Clout is derived primarily from:

  • social events (especially tease).
  • seen events (proof of contact).
  • hey-there / chau (presence).
  • observation (restarts and uptime).

6. Algorithms

Section titled “6. Algorithms”

Clout Derivation

Section titled “Clout Derivation”
  1. Base Score: 1.0.
  2. Interaction Bonus: For every relevant interaction in the ledger:
    • Score += InteractionValue * Resonance(Personality) * TimeDecay(Age).
  3. Resonance Calculation:
    • Social naras give more weight to tease and gossip.
    • Chill naras give less weight to high-restart counts.
    • Agreeable naras penalize excessive teasing.
  4. Time Decay:
    • Weight = 1.0 / (1.0 + Age/HalfLife).
    • Social events decay faster than “hard facts” like restarts.

7. Failure Modes

Section titled “7. Failure Modes”
  • Clout Bubbles: A small group of naras teasing each other can create a local “clout bubble” that may not be recognized by outsiders.
  • Amnesia: If a nara prunes too many social events, its clout rankings will shift toward those with more recent activity.

8. Security / Trust Model

Section titled “8. Security / Trust Model”
  • Sybil Resistance: Because clout is weighted by the observer’s own view of the emitter’s clout, new or unknown naras cannot easily manipulate the rankings.
  • Signature Required: Only signed events can contribute to clout.

9. Test Oracle

Section titled “9. Test Oracle”
  • TestClout_SubjectiveDivergence: Verifies that a Social nara and a Chill nara produce different rankings from the same event stream.
  • TestClout_Decay: Ensures that a nara who stops participating eventually loses its high clout score.
  • TestClout_Resonance: Validates that personality traits correctly amplify or dampen specific interaction types.

10. Open Questions / TODO

Section titled “10. Open Questions / TODO”
  • Implement “Global Clout” in the Web UI by averaging opinions from multiple naras.
  • Add “Negative Clout” for naras that frequently emit malformed or unverified events.