Project StoryMachine: Exploring implications of recommender based spatial hypertext systems for folklore and the humanities

• Antragstellerinnen / Antragsteller: Professor Dr. Claus Atzenbeck; Professorin Dr. Sarah Diefenbach; Professorin Dr. Astrid Ensslin
• Fachliche Zuordnung: Allgemeine und vergleichende Literaturwissenschaft; Kulturwissenschaft ; Datenmanagement, datenintensive Systeme, Informatik-Methoden in der Wirtschaftsinformatik
• Förderung: Förderung seit 2024
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 547532269

Project StoryMachine aims to preserve, explore and provide greater access to folklore traditions in Germany and the UK, through the development of a digital infrastructure called StoryMachine ("SM"). Folklore plays a vital role in shaping identity and fostering cultural understanding, but it faces archival and cultural challenges, particularly in an era of alternative truths and populist separatism. Existing digital efforts have primarily focused on archiving and digitizing rather than on in-depth exploration and analysis. Hence, they often prioritizze discrete collections over broader folkloric traditions, lack interactivity, and fail to capture evolving folklore and folk experiences. SM addresses these shortcomings by integrating spatial hypertext and recommender systems, creating a dynamic platform for interconnected folklore narratives. Familiar from commercial contexts like Amazon or Netflix, this use of recommender systems creates exciting, dynamic opportunities for information and archival studies, while spatial hypertext allows this emerging context to be visually and dynamically represented. This project will produce new insights into the relationships between folklore and identity construction by examining joint motifs, key differences, and commonalities in storytelling among participants from different geographic regions, cultural backgrounds and age groups. Integrating the Aarne-Thompson-Uther Index (a catalogue of folktale types widely used in folklore studies, "ATUI") with the SM system will enable new approaches to exploring folklore. Following the integration of ATUI with SM, the project will delve into augmenting folklore motifs through collaborative digital methods, critical motif analysis, evaluating community engagement in digital storytelling, and exploring the psychological aspects of interacting with such systems. SM’s innovative user interface fosters collaboration between users and the machine, empowering users and harnessing the co-creative potential of AI. The tools and methods developed through this project extend beyond folklore studies, impacting storytelling and narrative development across various fields, benefiting scholars, students, educators, and the wider public. This research also addresses fundamental questions about authorship and ownership in generative AI, advocating for a collaborative approach that emphasizes human-machine equality and is more context-sensitive and emergent compared to existing approaches. The project's impact extends to potential applications in various fields, reshaping knowledge cultures and communities. It brings together scholars from folklore studies, digital humanities, narrative studies, psychology, and computer science, fostering interdisciplinary collaboration to advance research and create new perspectives. SM contributes to the advancement of digital humanities, hypertext, and narrative studies by offering innovative tools for exploration, creativity, and collaboration.

• DFG-Verfahren: Sachbeihilfen
• Internationaler Bezug: Großbritannien
• Partnerorganisation: Arts and Humanities Research Council
• Kooperationspartnerin: Professorin Dr. Jane Winters