  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.

Human-Computer Interaction;Computation and Language;Computers and Society