Exploring a Gamified Personality Assessment Method through Interaction with Multi-Personality LLM Agents
- URL: http://arxiv.org/abs/2507.04005v1
- Date: Sat, 05 Jul 2025 11:17:20 GMT
- Title: Exploring a Gamified Personality Assessment Method through Interaction with Multi-Personality LLM Agents
- Authors: Baiqiao Zhang, Xiangxian Li, Chao Zhou, Xinyu Gai, Zhifeng Liao, Juan Liu, Xue Yang, Niqi Liu, Xiaojuan Ma, Yong-jin Liu, Yulong Bian,
- Abstract summary: This study explores an interactive approach for personality assessment, focusing on the multiplicity of personality representation.<n>We propose a framework of gamified personality assessment through multi-personality representations (Multi-PR GPA)
- Score: 40.48149639841564
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The execution of effective and imperceptible personality assessments is receiving increasing attention in psychology and human-computer interaction fields. This study explores an interactive approach for personality assessment, focusing on the multiplicity of personality representation. We propose a framework of gamified personality assessment through multi-personality representations (Multi-PR GPA). The framework leverages Large Language Models to empower virtual agents with diverse personalities. These agents elicit multifaceted human personality representations through engaging in interactive games. Drawing upon the multi-type textual data generated throughout the interaction, it achieves two ways of personality assessments (i.e., Direct Assessment and Que-based Assessment) and provides interpretable insights. Grounded in the classic Big Five theory, we implemented a prototype system and conducted a user study to assess the efficacy of Multi-PR GPA. The results underscore the effectiveness of our approach in personality assessment and demonstrate that it achieves superior performance when considering the multiplicity of personality representation.
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