Computer Science > Artificial Intelligence
arXiv:2603.09533 (cs)
[Submitted on 10 Mar 2026]
Title:Enhancing Debunking Effectiveness through LLM-based Personality Adaptation
View a PDF of the paper titled Enhancing Debunking Effectiveness through LLM-based Personality Adaptation, by Pietro Dell'Oglio and Alessandro Bondielli and Francesco Marcelloni and Lucia C. Passaro
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Abstract:This study proposes a novel methodology for generating personalized fake news debunking messages by prompting Large Language Models (LLMs) with persona-based inputs aligned to the Big Five personality traits: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness. Our approach guides LLMs to transform generic debunking content into personalized versions tailored to specific personality profiles. To assess the effectiveness of these transformations, we employ a separate LLM as an automated evaluator simulating corresponding personality traits, thereby eliminating the need for costly human evaluation panels. Our results show that personalized messages are generally seen as more persuasive than generic ones. We also find that traits like Openness tend to increase persuadability, while Neuroticism can lower it. Differences between LLM evaluators suggest that using multiple models provides a clearer picture. Overall, this work demonstrates a practical way to create more targeted debunking messages exploiting LLMs, while also raising important ethical questions about how such technology might be used.
| Comments: | |
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL) |
| Cite as: | arXiv:2603.09533 [cs.AI] |
| (or arXiv:2603.09533v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2603.09533
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| Related DOI: | https://doi.org/10.1007/978-3-032-15632-7_23
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Submission history
From: Alessandro Bondielli [view email][v1] Tue, 10 Mar 2026 11:44:17 UTC (1,579 KB)
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View a PDF of the paper titled Enhancing Debunking Effectiveness through LLM-based Personality Adaptation, by Pietro Dell'Oglio and Alessandro Bondielli and Francesco Marcelloni and Lucia C. Passaro
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