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

Rachelyn Farrell; Stephen G. Ware

doi:10.1007/978-3-319-48279-8_13

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

Rachelyn Farrell, Stephen G. Ware

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience 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 when a past event shares one or more of these indices with the most recently narrated event, that past event is more salient, or easier to recall, than an event which shares none of them. In this study we demonstrate that we can predict user choices based on the salience of past events. Specifically, we investigate the hypothesis that when users are given a choice between two events in an interactive narrative, they are more likely to choose the one which makes the previous events in the story more salient according to this theory.

Original language	English
Title of host publication	Interactive Storytelling - 9th International Conference on Interactive Digital Storytelling, ICIDS 2016
Editors	Andrew S. Gordon, Frank Nack
Pages	147-155
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-319-48279-8_13
State	Published - 2016
Event	9th International Conference on Interactive Digital Storytelling, ICIDS 2016 - Los Angeles, United States Duration: Nov 15 2016 → Nov 18 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10045 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th International Conference on Interactive Digital Storytelling, ICIDS 2016
Country/Territory	United States
City	Los Angeles
Period	11/15/16 → 11/18/16

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2016.

Keywords

Computational models of narrative
Indexter
Planning
Salience

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-48279-8_13

Cite this

Farrell, R., & Ware, S. G. (2016). Predicting user choices in interactive narratives using indexter’s pairwise event salience hypothesis. In A. S. Gordon, & F. Nack (Eds.), Interactive Storytelling - 9th International Conference on Interactive Digital Storytelling, ICIDS 2016 (pp. 147-155). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10045 LNCS). https://doi.org/10.1007/978-3-319-48279-8_13

Farrell, Rachelyn ; Ware, Stephen G. / Predicting user choices in interactive narratives using indexter’s pairwise event salience hypothesis. Interactive Storytelling - 9th International Conference on Interactive Digital Storytelling, ICIDS 2016. editor / Andrew S. Gordon ; Frank Nack. 2016. pp. 147-155 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Farrell, R & Ware, SG 2016, Predicting user choices in interactive narratives using indexter’s pairwise event salience hypothesis. in AS Gordon & F Nack (eds), Interactive Storytelling - 9th International Conference on Interactive Digital Storytelling, ICIDS 2016. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10045 LNCS, pp. 147-155, 9th International Conference on Interactive Digital Storytelling, ICIDS 2016, Los Angeles, United States, 11/15/16. https://doi.org/10.1007/978-3-319-48279-8_13

Predicting user choices in interactive narratives using indexter’s pairwise event salience hypothesis. / Farrell, Rachelyn; Ware, Stephen G.
Interactive Storytelling - 9th International Conference on Interactive Digital Storytelling, ICIDS 2016. ed. / Andrew S. Gordon; Frank Nack. 2016. p. 147-155 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10045 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience 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 when a past event shares one or more of these indices with the most recently narrated event, that past event is more salient, or easier to recall, than an event which shares none of them. In this study we demonstrate that we can predict user choices based on the salience of past events. Specifically, we investigate the hypothesis that when users are given a choice between two events in an interactive narrative, they are more likely to choose the one which makes the previous events in the story more salient according to this theory.

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Farrell R, Ware SG. Predicting user choices in interactive narratives using indexter’s pairwise event salience hypothesis. In Gordon AS, Nack F, editors, Interactive Storytelling - 9th International Conference on Interactive Digital Storytelling, ICIDS 2016. 2016. p. 147-155. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-48279-8_13

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

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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