Social Events

Social events enable naras to interact, judge, and participate in collective behaviors like trends and “buzz.” They turn cold network metrics into human-readable social narrative.

1. Purpose

• Create human-readable network activity for the UI and logs.
• Drive the subjective reputation system (Clout).
• Model collective behaviors (trends) and network energy (Buzz).
• Provide a basis for autonomous “drama” and interaction.

2. Conceptual Model

• SocialEvent: An interaction payload contained within a SyncEvent.
• Teasing: Subjective commentary or “jab” at a peer’s state or behavior.
• Buzz: A numerical metric representing the current “energy” or activity level of the network.
• Trends: Collective participation in shared movements or styles, influenced by personality.

Invariants

1. Subjective Resonance: A nara’s personality determines whether a social event is considered “meaningful” enough to be stored.
2. Anti-Pile-On: Jitter and ledger checks prevent multiple naras from emitting the exact same commentary simultaneously.
3. Cooldown: naras enforce a 5-minute local cooldown per target for specific interaction types.
4. Deterministic Interaction: The choice to tease or join a trend is influenced by the nara’s soul-derived traits.

3. External Behavior

• naras monitor the ledger for “teasable” moments (e.g., a peer reaching 69 restarts).
• naras join or leave trends based on their Agreeableness and the trend’s current popularity.
• The Web UI visualizes “Shooting Stars” and animations for social events to reflect network Buzz.

4. Interfaces

• SocialEventPayload: The payload structure for SyncEvent (type: social).
• BuzzProjection: Computes local and network-weighted buzz levels.
• TrendManager: Handles joining, starting, and abandoning trends.

5. Event Types & Schemas

social (SyncEvent Payload)

• type: tease, observed, gossip, observation, service.
• actor, actor_id: The nara initiating the interaction.
• target, target_id: The nara being interacted with.
• reason: The social trigger (e.g., nice-number, high-restarts).
• witness: Optional third-party nara reporting the event.

Tease Reasons

• high-restarts: Peer exceeds a specific restart threshold.
• comeback: Peer returns to ONLINE status after being MISSING.
• trend-abandon: Peer leaves a popular (>30%) trend.
• nice-number: Milestone or meme numbers (e.g., 42, 69, 100, 420).
• random: A rare, probabilistic “poke” to keep things interesting.

6. Algorithms

Buzz Calculation

• Local Buzz: Incremented by sent/received teases and joining trends.
• Decay: Buzz naturally decays over time (e.g., -3 every 10 seconds).
• Weighted Buzz: A combination of local activity, the average network buzz, and the maximum buzz reported by any peer.

Anti-Pile-On

To prevent redundant commentary:

1. When a trigger is detected, the nara waits for a random jitter delay (0-5s).
2. It then checks the ledger for any event with the same target and reason within the last 30 seconds.
3. If such an event exists, the nara aborts its own tease.

sequenceDiagram
    participant O as Observer
    participant L as Ledger
    Note over O: Trigger detected
    O->>O: Jitter Delay (0-5s)
    O->>L: Check for identical target+reason (last 30s)
    alt Found
        Note over O: Abort
    else Not Found
        O->>O: Emit Tease
    end

Trend Logic (Every 30s)

• Joining: Chance is a function of Agreeableness and the trend’s popularity.
• Starting: Chance is a function of Sociability.
• Rebel Trends: naras with very low Agreeableness may start “underground” trends when the dominant trend becomes too popular (>50%).

7. Failure Modes

• Buzz Saturation: If the network is extremely active, buzz may stay at its maximum level, losing its utility as a differentiator.
• Trend Stagnation: If every nara is highly Agreeable, the network may get stuck in a single permanent trend.

8. Security / Trust Model

• Authenticity: Social events must be signed by the actor.
• Hearsay: gossip type events are treated as lower-confidence data than direct observations.

9. Test Oracle

• TestTeaseCooldown: Ensures naras don’t tease the same target too frequently.
• TestNiceNumbers: Verifies that meme and milestone numbers correctly trigger teases.
• TestTrendTransition: Validates that Agreeableness correctly influences trend adoption.
• TestBuzzDecay: Confirms that the buzz level decreases when activity stops.

10. Open Questions / TODO

• Implement “Social Conflict” where naras with opposing traits have a higher chance of teasing each other.
• Link trend participation to Aura color modifiers.