An information-theoretic evaluation of narrative complexity for interactive writing support

• We evaluate narrative complexity from the information processing perspective.
• The knowledge flow reflects the information processing of narrative agents.
• The amount of information processed by recipients is used as a complexity measure.
• The proposed measure captures the characteristics of narratives at a content level.
• The evaluation method can support an author in the interactive writing process.

Narrative complexity should be managed systematically during the creation process because it heavily influences the levels of understanding and the interest of recipients. Existing research has tended to depend on impressionist criticism or to deal with narrative complexity at general and superficial levels. In this paper, we consider the creation and acceptance of narrative as information processing mediated by a narrative text. Under this assumption, we propose a method to quantitatively evaluate narrative complexity at the recipient's cognitive level, and to effectively utilize the evaluation to aid in the author's narrative creation process. Within our knowledge distribution model, a narrative is represented as a knowledge structure, and the knowledge state and knowledge flow of narrative agents are evaluated using a probabilistic reasoning model. From the knowledge flows, the amount of information processed and required by the recipient is calculated as a measure of the narrative complexity using entropy theory. As a case study, we conduct a comparative analysis of an actual cinematic narrative and a structurally manipulated version of that narrative to show how the method captures characteristics and changes of the narrative; we also discuss the improvements presented in this paper as compared to our previous research.