Towards a Formal Model of Narratives
This work addresses the need for computational tools in narratology, but it is incremental as it builds on existing formal modeling approaches.
The paper tackles the problem of formally modeling narratives by proposing a framework that captures information flow, reader model evolution, and uncertainty, and demonstrates its applicability through algorithms for measuring information accuracy and story coherence.
In this paper, we propose the beginnings of a formal framework for modeling narrative \textit{qua} narrative. Our framework affords the ability to discuss key qualities of stories and their communication, including the flow of information from a Narrator to a Reader, the evolution of a Reader's story model over time, and Reader uncertainty. We demonstrate its applicability to computational narratology by giving explicit algorithms for measuring the accuracy with which information was conveyed to the Reader and two novel measurements of story coherence.