This draft paper presents a workflow for creating User Personas with Large
Language Models, using the results of a Thematic Analysis of qualitative
interviews. The proposed workflow uses improved prompting and a larger pool of
Themes, compared to previous work conducted by the author for the same task.
This is possible due to the capabilities of a recently released LLM which
allows the processing of 16 thousand tokens (GPT3.5-Turbo-16k) and also due to
the possibility to offer a refined prompting for the creation of Personas. The
paper offers details of performing Phase 2 and 3 of Thematic Analysis, and then
discusses the improved workflow for creating Personas. The paper also offers
some reflections on the relationship between the proposed process and existing
approaches to Personas such as the data-driven and qualitative Personas.
Moreover, the paper offers reflections on the capacity of LLMs to capture user
behaviours and personality traits, from the underlying dataset of qualitative
interviews used for the analysis.

使用大型语言模型创建用户人物画像的工作流程，利用定性访谈的主题分析结果，提出了一个改进的提示和更大的主题池，以及对用户人物创建的工作流程进行了改进和反思，同时讨论了 LMM 捕捉用户行为和个性特征的能力。

使用定性访谈改进 LML 编写用户画像的指引和流程：捕捉用户的行为和人格特征

Improved prompting and process for writing user personas with LLMs,  using qualitative interviews: Capturing behaviour and personality traits of  users