AI Qualitative Interviews and Automated Thematic Coding: A Case Study for Three Policy-celated Topics
报告时间：2025年12月16日（周二）上午9:30—11:30
报告地点：文化中心305会议室
主讲人：山东大学 黄凌波教授
主持人：a漫
罗俊教授
Abstract：
With the rapid advancement of large language models (LLMs), the large scale application of qualitative interviews in economics has become feasible. This paper introduces a multi-agent LLM–based approach to semi-structured qualitative interviewing and develops a complete workflow built upon it. In this framework, AI agents serve as interviewers to conduct standardized yet probing semi-structured interviews. Subsequently, LLMs, assisted by human reviewers, extract thematic in sights and perform automated coding from the interview transcripts, thus achieving an integrated process from interviewing to coding. We implemented online interviews on three policy-relevant topics—fertility intentions, personal pension contributions, and stock market participation—and compared the performance of text-based and voice-based input modes. A total of 525 interviews were collected, with an average duration of 23 minutes each. The results indicate that, compared with one-off open ended questioning, AI-led interviews can systematically uncover participants’ mental models, reveal group heterogeneity, and produce results highly correlated with conven tional closed-form survey measures. Subjectively, over 95% of participants reported positive overall evaluations of the AI interviews, and their preference for AI inter viewers was significantly higher than for human interviewers. The entire interview and coding pipeline is replicable, auditable, and highly scalable. Finally, we discuss the practical challenges of applying this method in real-world settings and potential strategies to address them.
嘉宾简介：
黄凌波，山东大学经济研究院教授，博士生导师，山东大学杰出中青年学者。兼任中国运筹学会博弈分会副秘书长。主持国家自然科学基金优青项目。主要研究领域是行为与实验经济学、政治经济学、应用微观理论。研究主题包括人类合作与竞争行为、分配制度、大国竞合博弈、机制设计等。研究成果发表于Economic Journal（3篇）、Management Science（2篇）、Games and Economic Behavior（2篇）、Production and Operations Management等经济学与管理学领域国际顶级期刊。
