{ "_meta": { "description": "8x8 symmetric audience overlap matrix between competitor archetypes and the user creator. Values 0.0-1.0 represent fraction of shared audience (Jaccard intersection fraction). Used by propose_collab to compute collab reward multipliers and by query_creator_pool to expose overlap to the agent. Same-niche pairs ~0.4-0.65, cross-niche ~0.05-0.20.", "source": "Competitor pairs estimated from Rival IQ 2025 cross-industry overlap patterns + niche proximity heuristic. user_creator row tuned to a generic micro-creator (no locked niche): broad mass-market partners (lifestyle_blogger, viral_chaser) score highest; specialist partners (b2b_thought_leader, niche_expert) score lowest.", "mock_followers_note": "Mocked follower counts span tiers from micro (10k user) to mid (250k viral_chaser). Used to derive intersection size via Jaccard inversion: |A intersect B| = overlap * (|A| + |B|) / (1 + overlap)." }, "archetype_ids": ["niche_expert", "viral_chaser", "lifestyle_blogger", "b2b_thought_leader", "food_creator", "fitness_coach", "travel_creator", "user_creator"], "matrix": [ [1.00, 0.12, 0.10, 0.40, 0.08, 0.10, 0.15, 0.10], [0.12, 1.00, 0.55, 0.10, 0.20, 0.25, 0.30, 0.35], [0.10, 0.55, 1.00, 0.15, 0.30, 0.35, 0.40, 0.40], [0.40, 0.10, 0.15, 1.00, 0.08, 0.10, 0.12, 0.08], [0.08, 0.20, 0.30, 0.08, 1.00, 0.45, 0.35, 0.25], [0.10, 0.25, 0.35, 0.10, 0.45, 1.00, 0.30, 0.28], [0.15, 0.30, 0.40, 0.12, 0.35, 0.30, 1.00, 0.30], [0.10, 0.35, 0.40, 0.08, 0.25, 0.28, 0.30, 1.00] ], "niche_by_archetype": { "niche_expert": "tech", "viral_chaser": "lifestyle", "lifestyle_blogger": "lifestyle", "b2b_thought_leader": "business", "food_creator": "food", "fitness_coach": "fitness", "travel_creator": "travel", "user_creator": "generic" }, "mock_followers_by_archetype": { "niche_expert": 12000, "viral_chaser": 250000, "lifestyle_blogger": 11000, "b2b_thought_leader": 9000, "food_creator": 12000, "fitness_coach": 8000, "travel_creator": 11000, "user_creator": 10000 } }