PersonaGen: A Tool for Generating Personas from User Feedback
Xishuo Zhang, Lin Liu, Wang Yi, Xiao Liu, Hailong Wang, Anqi Ren, Chetan Arora
Abstract
Personas are crucial in software development processes, particularly in agile settings. However, no effective tools are available for generating personas from user feedback in agile software development processes. To fill this gap, we propose a novel tool that uses the GPT-4 model and knowledge graph to generate persona templates from well-processed user feedback, facilitating requirement analysis in agile software development processes. We developed a tool called PersonaGen. We evaluated PersonaGen using qualitative feedback from a small-scale user study involving student software projects. The results were mixed, highlighting challenges in persona-based educational practice and addressing non-functional requirements.