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Using AI for User Representation: An Analysis of 83 Persona Prompts
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本文分析了27篇使用大型语言模型生成用户画像的研究,发现主要生成单一画像,多采用文本和数字格式,并探讨计算化用户画像的潜在影响。

arXiv:2508.13047v1 Announce Type: cross Abstract: We analyzed 83 persona prompts from 27 research articles that used large language models (LLMs) to generate user personas. Findings show that the prompts predominantly generate single personas. Several prompts express a desire for short or concise persona descriptions, which deviates from the tradition of creating rich, informative, and rounded persona profiles. Text is the most common format for generated persona attributes, followed by numbers. Text and numbers are often generated together, and demographic attributes are included in nearly all generated personas. Researchers use up to 12 prompts in a single study, though most research uses a small number of prompts. Comparison and testing multiple LLMs is rare. More than half of the prompts require the persona output in a structured format, such as JSON, and 74% of the prompts insert data or dynamic variables. We discuss the implications of increased use of computational personas for user representation.

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大型语言模型 用户画像 研究分析
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