This second edition provides an overview of the principal problems, approaches, and challenges in modeling the narrative structure of stories. The book builds upon the prior edition by incorporating an additional focus on generative artificial intelligence and its applications for narratology. The author explains the computational representations of narrative elements, such as characters, events, causality, and time, proposing new methods for representing embedded narratives, fictional entities, tempo, and audience response. The book discusses the rise of generative AI systems, including large language models and transformers. The author explores the current applications of these systems and the extent to which they can be used to automate the cognitive aspects of narrative understanding and generation.

Presents an accessible primer on narratology for computer scientists, linguists, and digital humanities researchers Includes a thorough account of generative AI tools and their applications for narrative understanding and generation Discusses outstanding challenges that need to be addressed and directions for future advancements

Autorentext

Inderjeet Mani, Ph.D., is a Research Scientist specializing in natural language processing and artificial intelligence. He has worked at Yahoo (as a Senior Director), Georgetown University (Associate Professor), and MITRE (Senior Principal Scientist), and he has also been a visiting scientist at several other institutions. Dr. Mani has published over 100 scientific papers and six academic books, along with nearly 50 literary works including two novels. His research in NLP has included foundational work in narrative modeling, automatic summarization, and temporal and spatial information extraction.

Inhalt

Introduction.- Generative AI.- Narratological Background.- Time and Events.- Characters and Plans.- Plot.- Stories with Generative AI.- Summary and Future Directions.