In the Garden of Forking Paths: Mapping and Making Sense of Storytelling at Scale (Maria Antoniak)

Humans tell stories for many different purposes — to drive social movements, build trust, make sense of the world — and increasingly, we tell stories with and about AI. In this talk, I argue that instead of building benchmarks for AI-generated stories, we need descriptive, analytical methods for exploring and mapping narrative space. I present a series of projects that chart where storytelling happens and how it is changing by locating stories across online communities, characterizing narrative content in web-scale LLM pretraining data, and tracing how people iteratively generate and edit fiction in real user-chatbot conversations. This work reveals narrative axes that organize pretraining data, “solipsistic reader-writers” who obsessively regenerate the same stories in loops with chatbots, and edit trees representing the “forking paths” that people trace when exploring narrative space. The future study of storytelling needs more mixed-methods and cross-disciplinary collaboration, open and auditable data and models, and room to craft our own stories. Co-sponsored by the Berkeley Institute for Data Science and the School of Information Speaker Maria Antoniak Assistant Professor of Computer Science University of Colorado Boulder Maria Antoniak is an assistant professor of computer science at the University of Colorado Boulder. She is also affiliated with the Department of Information Science and is a member of the Boulder NLP Group. Her research focuses on natural language processing (NLP) and cultural analytics, with applications to online communities, healthcare, and the humanities. She creatively re-purposes computational text methods for human and high-stakes contexts, to study narratives, culture, and society. More info: https://www.ischool.berkeley.edu/events/cultural-analytics/2026/garden-forking-paths-mapping-and-making-sense-storytelling-scale