Exploring Creator-Centric Methods for LLM-Assisted Interactive Storytelling

While large language models (LLMs) are increasingly applied in creative domains, their role in supporting interactive storytelling tailored to creators’ needs remains underexplored. This thesis adopts a creator-centered perspective to examine how LLMs can assist in building interactive narratives, focusing on multi-layered structure editing, automated analysis, target user feedback, and the preservation of authorial control. A multi-stage design was employed: interviews with sixteen creators identified five key design goals, which informed the development of CoNoder, a prototype integrating node-graph editing, dual interaction modes, and generation styles, ripple-effect analysis, and simulated feedback. Evaluation results show that CoNoder improves creative efficiency, supports morally complex storytelling, and provides structured narrative feedback, though onboarding, expert guidance, and finer control remain areas for improvement. Overall, this research contributes a creator-focused framework and a practical system design approach, highlighting the need for future tools that balance expressive freedom with creative sovereignty.