Emotional Labor Strategy Preferences in LLM Personas

2026-08-31

AI Summary

研究通过构建包含500个社交场景的数据集，利用注入心理测量人格的大语言模型，探讨了不同人格特质对情绪劳动策略偏好的影响。

Abstract

Emotional labor is the effortful management of emotional displays to meet social or professional expectations. Personality traits have been correlated with emotional labor strategies, yet research on this link relies almost exclusively on self-report scales administered only in occupational settings. We investigate whether large language models injected with psychometrically grounded personas reproduce these personality-driven selection patterns across everyday social scenarios. We construct the first emotional labor strategy dataset of 500 socially situated events, each offering three behavioral choices corresponding to surface acting, deep acting, and genuine expression. We source 50 fictional characters from a large-scale personality repository and profile each through two parallel tracks: observer-rated bipolar adjective composites and in-character self-report items. Five LLMs evaluate all scenarios under both persona conditions. We find that models align more towards deep acting, and that Conscientiousness and Emotional Stability consistently predict this preference. Entropy analysis confirms that persona reliably influences the output and varies across models and emotions.

Problem

• emotional labor
• personality traits
• large language models
• social scenarios

Innovation

• large language models
• emotional labor strategies
• personas
• deep acting
• psychometrically grounded