IntervenSim is an intervention-aware social network simulation that couples source interventions with crowd interactions in a feedback loop, improving MAPE by 41.6% and DTW by 66.9% over prior static frameworks on real-world events.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Role-based personas in multi-agent LLM systems suppress payoff-aligned behavior, shifting equilibrium selection by up to 90 percentage points in Tragedy of the Commons versus Green Transition scenarios even with full payoff information.
citing papers explorer
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IntervenSim: Intervention-Aware Social Network Simulation for Opinion Dynamics
IntervenSim is an intervention-aware social network simulation that couples source interventions with crowd interactions in a feedback loop, improving MAPE by 41.6% and DTW by 66.9% over prior static frameworks on real-world events.
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When Identity Overrides Incentives: Representational Choices as Governance Decisions in Multi-Agent LLM Systems
Role-based personas in multi-agent LLM systems suppress payoff-aligned behavior, shifting equilibrium selection by up to 90 percentage points in Tragedy of the Commons versus Green Transition scenarios even with full payoff information.