Do Emotions Really Affect Argument Convincingness? A Dynamic Approach with LLM-based Manipulation Checks

Emotions have been shown to play a role in argument convincingness, yet this aspect is underexplored in the natural language processing (NLP) community.Unlike prior studies that use static analyses, focus on a single text domain or language, or treat emotion as just one of many factors, we introduce a dynamic framework inspired by manipulation checks commonly used in psychology and social science; leveraging LLM-based manipulation checks, this framework examines the extent to which perceived emotional intensity influences perceived convincingness.Through human evaluation of arguments across different languages, text domains, and topics, we find that in over half of cases, human judgments of convincingness remain unchanged despite variations in perceived emotional intensity; when emotions do have an impact, they more often enhance rather than weaken convincingness.We further analyze whether 11 LLMs behave like humans in the same scenario, finding that while LLMs generally mirror human patterns, they struggle to capture nuanced emotional effects in individual judgments.( !(), ) (, ) Topic: A Bill to prohibit the sale and advertising of activities abroad which involve low standards of welfare for animals.

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Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.1250
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Do Emotions Really Affect Argument Convincingness? A Dynamic Approach with LLM-based Manipulation Checks

Yanran Chen, Steffen Eger
1 links
Hate Speech and Cyberbullying Detection
article

Do Emotions Really Affect Argument Convincingness? A Dynamic Approach with LLM-based Manipulation Checks

Yanran Chen, Steffen Eger
article en

Abstract

Emotions have been shown to play a role in argument convincingness, yet this aspect is underexplored in the natural language processing (NLP) community.Unlike prior studies that use static analyses, focus on a single text domain or language, or treat emotion as just one of many factors, we introduce a dynamic framework inspired by manipulation checks commonly used in psychology and social science; leveraging LLM-based manipulation checks, this framework examines the extent to which perceived emotional intensity influences perceived convincingness.Through human evaluation of arguments across different languages, text domains, and topics, we find that in over half of cases, human judgments of convincingness remain unchanged despite variations in perceived emotional intensity; when emotions do have an impact, they more often enhance rather than weaken convincingness.We further analyze whether 11 LLMs behave like humans in the same scenario, finding that while LLMs generally mirror human patterns, they struggle to capture nuanced emotional effects in individual judgments.( !(), ) (, ) Topic: A Bill to prohibit the sale and advertising of activities abroad which involve low standards of welfare for animals.

Lutheran University of Applied Sciences Nuremberg (DE)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung
Reduced inequalities
Openalex Percentile: Top 90%
Hate Speech and Cyberbullying Detection
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Do Emotions Really Affect Argument Convincingness? A Dynamic Approach with LLM-based Manipulation Checks — Yanran Chen, Steffen Eger · (2025) | TGRS Research Map | TGRS