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ARGUS: Seeing the Influence of Narrative Features on Persuasion in Argumentative Texts

arXiv 2602.24109 ↗First posted 27 Feb 2026cs.CL cs.AIcited by 0

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Abstract (arXiv)

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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References · 6

  1. 2022The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluationcited by 133
  2. 2021Toward a Perspectivist Turn in Ground Truthing for Predictive Computingcited by 129
  3. 2016Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussionscited by 106
  4. 2023Where Do People Tell Stories Online? Story Detection Across Online Communitiescited by 16
  5. 2024On Classification with Large Language Models in Cultural Analyticscited by 9
  6. 2024AutoPersuade: A Framework for Evaluating and Explaining Persuasive Argumentscited by 7

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