IntervenSim: Intervention-Aware Social Network Simulation for Opinion Dynamics
2026-04-09T08:52:18Z•0d85f1d357f0a31d93802608f4ce469877fae59ad19b8b2815abac50f1044e08
LLM-safetyarxivclimate-misinformationdatasetdisinformationemoji-biasinfluence-operationsopen-source-coderepresentational-harmsresearch-papersocial-mediasocial-simulation
What happened
This arXiv feed collects multiple papers (Apr 2026) with several security-relevant findings: (1) IntervenSim: an "intervention-aware" social-network simulator that models source-side interventions and crowd feedback to better reproduce event trajectories (improves MAPE 41.6%, DTW 66.9% over prior work); (2) MF-MDP: a micro–macro social simulation framework that models per-agent latent states for long-horizon simulations (code published at github.com/AI4SS/MF-MDP), enabling stable simulations of far more interactions than prior LLM-based approaches; (3) a study releasing a large Brazilian YouTu
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- 0d85f1d357f0a31d93802608f4ce469877fae59ad19b8b2815abac50f1044e08
- Enrichment time
- 2026-04-09T08:52:18Z
- AI-assisted enrichment
- Yes
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