A six-role multi-LLM communication framework generates persuasive dialogue data that human judges find nearly indistinguishable from human-written rewrites.
Argument Strength is in the Eye of the Beholder: Audience Effects in Persuasion
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abstract
Americans spend about a third of their time online, with many participating in online conversations on social and political issues. We hypothesize that social media arguments on such issues may be more engaging and persuasive than traditional media summaries, and that particular types of people may be more or less convinced by particular styles of argument, e.g. emotional arguments may resonate with some personalities while factual arguments resonate with others. We report a set of experiments testing at large scale how audience variables interact with argument style to affect the persuasiveness of an argument, an under-researched topic within natural language processing. We show that belief change is affected by personality factors, with conscientious, open and agreeable people being more convinced by emotional arguments.
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2025 1verdicts
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Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication
A six-role multi-LLM communication framework generates persuasive dialogue data that human judges find nearly indistinguishable from human-written rewrites.