Predicting Convincingness in Political Speech: How Emotional Tone Shapes Persuasive Strength

Bhuvanesh Verma, Mounika Marreddy, Alexander Mehler


Abstract
Emotional tone plays a central role in persuasion, yet its impact on computational assessments of political argument quality in real world election campaign speeches remains understudied. In this work, we investigate whether positive emotional framing correlates with higher perceived convincingness in political arguments. We fine-tune language models on argument quality datasets and test their ability to transfer convincingness predictions to real-world campaign speeches. Using a corpus of U.S. presidential campaign speeches, we analyze emotional polarity in relation to predicted persuasive strength to test whether positively framed arguments are judged more convincing than neutral or negative ones. Our empirical analysis shows that political parties rely heavily on argumentation during their election campaigns. Also, we found the evidence that politicians strategically employ emotional cues within their arguments during these campaign speeches, with positive emotions being more strongly associated with persuasive strength, for example in topics such as USMCA’s Effect on American Jobs and Agriculture, Border Control Policies, Progressive Tax Reforms. At the same time, we find that negative emotions have a weaker yet still non-negligible influence on voter persuasion in topics such as City Crime and Civil Unrest and White Supremacist Violence (Charlottesville Incident).
Anthology ID:
2026.wassa-1.4
Volume:
The Proceedings for the 15th Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA 2026)
Month:
March
Year:
2026
Address:
Rabat, Morocco
Editors:
Jeremy Barnes, Valentin Barriere, Orphée De Clercq, Roman Klinger, Célia Nouri, Debora Nozza, Pranaydeep Singh
Venues:
WASSA | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
37–51
Language:
URL:
https://aclanthology.org/2026.wassa-1.4/
DOI:
Bibkey:
Cite (ACL):
Bhuvanesh Verma, Mounika Marreddy, and Alexander Mehler. 2026. Predicting Convincingness in Political Speech: How Emotional Tone Shapes Persuasive Strength. In The Proceedings for the 15th Workshop on Computational Approaches to Subjectivity, Sentiment Social Media Analysis (WASSA 2026), pages 37–51, Rabat, Morocco. Association for Computational Linguistics.
Cite (Informal):
Predicting Convincingness in Political Speech: How Emotional Tone Shapes Persuasive Strength (Verma et al., WASSA 2026)
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PDF:
https://aclanthology.org/2026.wassa-1.4.pdf