Influencing user choices in interactive narratives using indexter’s pairwise event salience hypothesis

Rachelyn Farrell, Stephen G. Ware

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017
Pages37-42
Number of pages6
ISBN (Electronic)9781577357919
StatePublished - 2017
Event13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017 - Snowbird, Little Cottonwood Canyon, United States
Duration: Oct 5 2017Oct 9 2017

Publication series

NameProceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

Conference

Conference13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017
Country/TerritoryUnited States
CitySnowbird, Little Cottonwood Canyon
Period10/5/1710/9/17

Bibliographical note

Publisher Copyright:
Copyright © 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

Funding

This research was supported by NSF award IIS-1464127.

FundersFunder number
National Science Foundation (NSF)IIS-1464127

    ASJC Scopus subject areas

    • Visual Arts and Performing Arts
    • Artificial Intelligence

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