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

TL;DR

ARGUS, a framework for studying the impact of narration on persuasion in argumentative discourse, is presented, integrating insights from two established theoretical frameworks that capture both textual narrative features and their effects on recipients.

Abstract

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.

Figures (6)

• Figure 1: An example ChangeMyView discussion thread. The original poster User 001 expresses a belief, and other users respond. User 002 received a delta, indicating their comment successfully changed the original poster's view.
• Figure 2: An example of Story and Story features.
• Figure 3: Distribution of the strength of Story occurrence and Story features.
• Figure 4: Distribution of the features' strength scores calculated as the average of the annotators' ratings.
• Figure 5: The distribution of narrativity scores per delta status in the ChangeMyView corpus.