Our feeds shouldn't value confrontational engagement over complementary content, nor should they obsequiously feed us only content we agree with. They should strike a balance and mend social disagreements rather than make them worse. — Michael Bernstein, Stanford HAI Senior Fellow
Interactive Objective

Recommendation Function

Bridging Weight (λ = 0.75)
Outrage Penalty (γ = 0.60)
Simulated User Feed (Target: Agent_04 (Left)) 8 Ranked Posts
Simulated 16-Agent Network

Attitude Drift & Cross-Group Interplay

Inter-group Tension 0.24 -0.54 vs baseline
Feed Diversity 68.5% Information breadth
Consensus Overlap 0.74 Bernstein Index
Outrage Exposure 0.19 Virality dampening
Cluster A (Reformist)
Cluster B (Traditionalist)
Bridging Edge (Shared nuance)
Hostile / Weak tie

Complementary Bridging Active

Under Bernstein’s Bridging model, posts receive algorithmic priority if they are evaluated favorably across divergent clusters, penalizing pure partisan virality. Instead of isolating users in echo chambers or sparking outrage via provocation, feeds surface unaligned arguments that resonate across ideological divides.

Scoring Matrix: 20 Candidate Posts Calculated per objective function
ID Author Stance Outrage Bridge Score Rank Score