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Interactive Digital Narratives (IDNs) is an interdisciplinary research area related mainly to Narrative Studies, Design, Human-Computer Interaction, and Gaming. In this field, empirical investigations on using Artificial Intelligence (AI) support systems for creating IDNs are growing, demonstrating the value of exploring their potential. However, a systematic categorization of AI support system features and key elements is missing. This paper addresses this gap by presenting an analytical framework to describe and map such systems. The analytical framework is the result of multimethod qualitative approach, that combines mainly case study analysis with interviews. A total of 60 empirical investigations retrieved through academic and grey literature have been collected and analyzed, enabling to identify: AI support systems' types (AI-based Creative Support Tools, AI Authoring Systems, and AI Support Systems for Interactive Digital Narratives) and categories (AI system structure, Creativity, Interaction, and Narratives). A cross-case analysis of seven selected exemplary cases of the type AI Support Systems for Interactive Digital Narratives reveals needs, challenges, and research opportunities to fulfil. The main contribution of the framework for researchers, practitioners, and designers is its use as an analytical and generative tool to acknowledge existing and future AI support systems for creating IDNs.
Șerbănescu et al. (Tue,) studied this question.