Writing user personas with Large Language Models: Testing phase 6 of a Thematic Analysis of semi-structured interviews
This addresses the problem of automating user persona creation for User Centered Design processes, but it is incremental as it builds on prior work and focuses on a specific phase.
The paper tested whether GPT-3.5-Turbo can satisfactorily perform Thematic Analysis (TA) on semi-structured interviews, specifically focusing on phase 6 to write user personas, and found that the model can build basic user personas with acceptable quality and generate ideas for them.
The goal of this paper is establishing if we can satisfactorily perform a Thematic Analysis (TA) of semi-structured interviews using a Large Language Model (more precisely GPT3.5-Turbo). Building on previous work by the author, which established an embryonal process for conducting a TA with the model, this paper will perform a further analysis and then cover the last phase of a TA (phase 6), which entails the writing up of the result. This phase was not covered by the previous work. In particular, the focus will be on using the results of a TA done with the LLM on a dataset of user interviews, for writing user personas, with the model building on the TA to produce the personas narratives. User personas are models of real users, usually built from a data analysis like interviews with a sample of users. User personas are tools often used in User Centered Design processes. The paper shows that the model can build basic user personas with an acceptable quality deriving them from themes, and that the model can serve for the generation of ideas for user personas.