Narrative generation for suspense: Modeling and evaluation

Abstract

Although suspense contributes significantly to the enjoyment of a narrative by its readers, there has been little research on the automated generation of stories that evoke specific cognitive and affective responses in their readers. The goal of this research is to develop and evaluate a system that produces a narrative designed specifically to evoke suspense from the reader. The system takes as input a plan data structure representing the goals of a storyworld's characters and the actions they perform in pursuit of them. Adapting theories developed by cognitive psychologists, the system uses a plan-based model of narrative comprehension to determine the final content of the story in order to heighten a reader's level of suspense. This paper outlines the various components of the system and describes an empirical evaluation. The evaluation provides strong support for the claim that the system is effective in generating suspenseful stories. © 2008 Springer Berlin Heidelberg.