分析故事特征如何影响论辩说服力，发现关键叙事要素。
ARGUS: Seeing the Influence of Narrative Features on Persuasion in Argumentative Texts
- 构建新框架ARGUS，标注故事存在与六类叙事特征。
- 通过大模型和分类器发现：特定叙事特征显著提升说服成功率。
- 适合研究网络论辩、传播效果与生成式AI的学者与工程师。
故事能否增强论点的说服力？哪些叙事特征最为关键？尽管故事常被视为有力的说服工具，其在在线非结构化论辩中的具体作用仍不明确。为此，我们提出ARGUS框架，用于研究叙事对论辩话语说服力的影响。ARGUS引入一个新数据集ChangeMyView，标注了故事存在性及六项关键叙事特征，并融合两个成熟理论框架，涵盖文本叙事特征及其对受众的影响。利用编码器分类器与零样本大语言模型（LLMs），ARGUS可大规模识别故事与叙事特征，并分析不同叙事维度如何影响在线论辩中的说服成功。实验表明，特定叙事特征显著提升说服力，为理解数字时代说服机制提供新视角。
原文摘要 · Abstract (English)
Can narratives make arguments more persuasive? And to this end, which narrative features matter most? Although stories are often seen as powerful tools for persuasion, their specific role in online, unstructured argumentation remains underexplored. To address this gap, we present ARGUS, a framework for studying the impact of narration on persuasion in argumentative discourse. ARGUS introduces a new ChangeMyView corpus annotated for story presence and six key narrative features, integrating insights from two established theoretical frameworks that capture both textual narrative features and their effects on recipients. Leveraging both encoder-based classifiers and zero-shot large language models (LLMs), ARGUS identifies stories and narrative features and applies them at scale to examine how different narrative dimensions influence persuasion success in online argumentation.
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