LLM action selection approximates but does not reliably preserve a reference first-order Markov policy in OSN simulations and runs several hundred times slower.
URL http://arxiv.org/abs/2502.01450
4 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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LLM agents calibrated on Italian election data produce coherent posts and realistic network structure but show less tone and toxicity variation than real users, with opinion changes resembling traditional mathematical models.
Agentic AI needs social theory as structural priors in the MASS framework to model emergent dynamics from multi-agent interactions.
LLMs fail to emulate human belief dynamics: they mismatch initial distributions and show higher conformity than humans in network interactions.
citing papers explorer
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Should LLM Agents Decide in Social Simulations? Comparing Finite-State and LLM-Based Decision Policies
LLM action selection approximates but does not reliably preserve a reference first-order Markov policy in OSN simulations and runs several hundred times slower.
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Simulating Online Social Media Conversations on Controversial Topics Using AI Agents Calibrated on Real-World Data
LLM agents calibrated on Italian election data produce coherent posts and realistic network structure but show less tone and toxicity variation than real users, with opinion changes resembling traditional mathematical models.
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Social Theory Should Be a Structural Prior for Agentic AI: A Formal Framework for Multi-Agent Social Systems
Agentic AI needs social theory as structural priors in the MASS framework to model emergent dynamics from multi-agent interactions.
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Can LLMs Emulate Human Belief Dynamics?
LLMs fail to emulate human belief dynamics: they mismatch initial distributions and show higher conformity than humans in network interactions.