Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience—or prominence in memory—of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that a past event is more salient if it shares one or more of these indices with the most recently narrated event. In a previous study we used this model to predict users’ choices in an interactive story based on the indices of prior events. We now show that we can use the same method to influence them to make certain choices. In this study, participants read an interactive story with two possible endings. We influenced them to choose a particular ending by manipulating the salience of story events. We showed that users significantly favored the targeted ending.
Rachelyn Farrell, Stephen G. Ware. Influencing user choices in interactive narratives using Indexter’s pairwise event salience hypothesis. In Proceedings of the 13th AAAI International Conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 37-42, 2017.