How topic content shapes LLM personality-tailored persuasion: semantic anchoring and topic stereotype effects

Large language models (LLMs) have shown promise in generating personality-tailored persuasive messages, yet their effectiveness remains inconsistent across contexts. This research systematically investigated how the characteristics of recommended products or actions shapes the efficacy of LLM- generated personality-tailored persuasion through three experimental studies (N = 618). Study 1 revealed that personality-matching effects were limited and inconsistent when the core features of the recommended product or action were not controlled. Qualitative analysis suggested that uncontrolled semantic variation across personality framings obscured persuasive effects. Study 2 demonstrated that explicitly anchoring messages to core product or action features-while allowing stylistic variation-produced robust personality-matching effects across multiple traits and topics. Study 3 extended findings across diverse domains (health, consumer products, entertainment, prosocial behavior) and confirmed that topic-specific stereotypes systematically influence message effectiveness independent of recipient personality. Messages aligning with widely shared topic expectations (e.g., high-Extraversion framing for music festivals, high-Agreeableness framing for donations) were preferred across audiences regardless of individual traits. These findings reveal two critical boundary conditions for LLM-based personalized persuasion: stabilizing core content through semantic anchoring facilitates the emergence of personality-matching effects, and topic stereotypes create baseline preferences that may amplify or attenuate personalization benefits. Practically, effective implementation requires anchoring core content while modulating style, and evaluating topic stereotypes before applying trait customization. This work clarifies when and how generative AI can reliably enhance persuasive communication across mental health, public health, and consumer domains. Study 3 extended the findings across diverse domains (health, consumer products, entertainment, and prosocial behavior) and suggested a consistent role of topic-specific stereotypes in shaping message effectiveness, above and beyond recipient personality.

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Publication Details

Journal
Frontiers in Psychiatry
Published
2026-01-30
DOI
https://doi.org/10.3389/fpsyt.2026.1756792
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
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article

How topic content shapes LLM personality-tailored persuasion: semantic anchoring and topic stereotype effects

Zili Zhou, Shuai Xu, Nan Zhao
Frontiers in Psychiatry
Mental Health via Writing
article

How topic content shapes LLM personality-tailored persuasion: semantic anchoring and topic stereotype effects

Zili Zhou, Shuai Xu, Nan Zhao
article en

Abstract

Large language models (LLMs) have shown promise in generating personality-tailored persuasive messages, yet their effectiveness remains inconsistent across contexts. This research systematically investigated how the characteristics of recommended products or actions shapes the efficacy of LLM- generated personality-tailored persuasion through three experimental studies (N = 618). Study 1 revealed that personality-matching effects were limited and inconsistent when the core features of the recommended product or action were not controlled. Qualitative analysis suggested that uncontrolled semantic variation across personality framings obscured persuasive effects. Study 2 demonstrated that explicitly anchoring messages to core product or action features-while allowing stylistic variation-produced robust personality-matching effects across multiple traits and topics. Study 3 extended findings across diverse domains (health, consumer products, entertainment, prosocial behavior) and confirmed that topic-specific stereotypes systematically influence message effectiveness independent of recipient personality. Messages aligning with widely shared topic expectations (e.g., high-Extraversion framing for music festivals, high-Agreeableness framing for donations) were preferred across audiences regardless of individual traits. These findings reveal two critical boundary conditions for LLM-based personalized persuasion: stabilizing core content through semantic anchoring facilitates the emergence of personality-matching effects, and topic stereotypes create baseline preferences that may amplify or attenuate personalization benefits. Practically, effective implementation requires anchoring core content while modulating style, and evaluating topic stereotypes before applying trait customization. This work clarifies when and how generative AI can reliably enhance persuasive communication across mental health, public health, and consumer domains. Study 3 extended the findings across diverse domains (health, consumer products, entertainment, and prosocial behavior) and suggested a consistent role of topic-specific stereotypes in shaping message effectiveness, above and beyond recipient personality.

Frontiers in PsychiatryVol. 17
Chinese Academy of Sciences (CN), Czech Academy of Sciences, Institute of Psychology (CZ), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 77%
Mental Health via Writing
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