Persona Alchemy: Designing, Evaluating, and Implementing Psychologically-Grounded LLM Agents for Diverse Stakeholder Representation

Published: 02 Mar 2026, Last Modified: 18 Apr 2026AFAA 2026 PosterEveryoneRevisionsBibTeXCC BY 4.0
Track: Tiny/Short Papers Track (up to 3 pages)
Keywords: NLP and Psychological Theory, Social Cognitive Framework for LLMs, Stakeholder Representation, Persona Evaluation, Interdisciplinary Agent Design, Persona Modeling, Human-AI Alignment
TL;DR: We developed a psychology-based framework for LLM agents that creates consistent stakeholder personas capable of appropriate persona adaptation when faced with contradicting information.
Abstract: Despite advances in designing personas for Large Language Models (LLM), challenges remain in aligning them with human cognitive processes and representing diverse stakeholder perspectives. We introduce a Social Cognitive Theory (SCT) agent design framework for designing, evaluating, and implementing psychologically grounded LLMs with consistent behavior. Our framework operationalizes SCT through four personal factors (cognitive, motivational, biological, and affective) for designing, six quantifiable constructs for evaluating, and a graph database-backed architecture for implementing stakeholder personas. Experiments tested agents' responses to contradicting information of varying reliability. In the highly polarized renewable energy transition discourse, we design five diverse agents with distinct ideologies, roles, and stakes to examine stakeholder representation. The evaluation of these agents in contradictory scenarios occurs through comprehensive processes that implement the SCT. Results show consistent response patterns ($R^2$ range: $0.58-0.61$) and systematic temporal development of SCT construct effects. Principal component analysis identifies two dimensions explaining 73% of variance, validating the theoretical structure. Our framework offers improved explainability and reproducibility compared to black-box approaches. This work contributes to ongoing efforts to improve diverse stakeholder representation while maintaining psychological consistency in LLM personas.
Submission Number: 44
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