IntervenSim: Intervention-Aware Social Network Simulation for Opinion Dynamics

2026-04-09T08:52:18Z0d85f1d357f0a31d93802608f4ce469877fae59ad19b8b2815abac50f1044e08
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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