用角色扮演+AI分析，挖掘用户隐性道德观，让需求工程更懂人心。

This study presents a proof of concept for eliciting and representing the moral profiles of digital system users in Requirements Engineering (RE) by combining immersive role-playing games (RPGs) with large language model (LLM) analysis. While existing approaches rely on predefined value taxonomies and explicit articulation, values are often tacit, context-dependent, and difficult to express directly. To address these limitations, we propose moving from the elicitation of discrete moral values to the narrative reconstruction and representation of users' moral profiles. Grounded in phenomenological and narrative anthropology, the approach focuses on capturing users' moral orientations as they emerge through situated decision-making. RPG sessions generate context-rich narrative data, which are then analyzed by a specialized LLM (GPT-A) to produce individual anthropological moral profiles (IAMPs). A validation process based on cross-comparison between model outputs and participants' responses in unseen moral scenarios assesses the adequacy of the generated representations. Results indicate that RPG environments effectively support the generation of rich, context-dependent data for eliciting tacit values, and that an anthropologically grounded LLM can transform such data into coherent narrative representations of users' moral profiles. These representations enable the contextual interpretation of users' preferences and values within the given domain, with improved performance when interpretive framing captures relationships between actions, underlying motivations, and individual domain expertise. From an RE perspective, this approach enables the analysis of user preferences and trade-offs while preserving their situated and dynamic nature, providing a foundation for integrating human moral values into the early stages of RE.