PERSUASIONTRACE introduces a Bayesian-network simulated target for multi-turn persuasion that matches human belief dynamics (81 vs 80) better than LLM baselines (64) and enables process-level evaluation.
Bakker, Daniel Jarrett, Hannah Sheahan, Martin J
11 Pith papers cite this work. Polarity classification is still indexing.
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Hybrid human-AI networks in 5x5 grids reached lower final polarization than human-only networks after eight rounds of opinion revision on polarizing topics.
LLMimic role-play training improves AI literacy and reduces susceptibility to AI persuasion across realistic scenarios.
LLMs exhibit higher perplexity on far-right and nationalist party texts than social-democratic ones, consistent across models and languages with correlation to translation metrics.
Agora uses AI to ground policy discussions in real human voices and a small study shows it improves users' perspective-taking compared to numerical summaries alone.
An experiment found LLM counterarguments improved group flexibility and satisfaction while AI mediation boosted minority participation but lowered psychological safety.
LLM facilitation in group charity allocation leaves consensus and participation equity unchanged while shifting specific allocations up to 5.5 points and increasing perceived trust.
An AI system that elicits personal experiences and visualizes policy support increased perceived legitimacy and perspective-taking in collective decisions despite unfavorable outcomes.
A survey-experiment with 236 participants shows most believe myths about gig worker vulnerabilities and that targeted counterarguments can reduce those beliefs.
A three-dimensional decision matrix concludes that AI-simulated focus groups cannot replace human ones for observing emergent political meanings and identities but may be conditionally suitable for testing campaign messages depending on risk and grounding.
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Train Yourself as an LLM: Exploring Effects of AI Literacy on Persuasion via Role-playing LLM Training
LLMimic role-play training improves AI literacy and reduces susceptibility to AI persuasion across realistic scenarios.