Comparing Player Responses To Choice-Based Interactive Narratives Using Facial Expression Analysis
Keywords
Analyses and evaluation of systems; Emotion; Facial expression analysis; Interactive storytelling; Media annotation
Abstract
Interactive storytelling balances the desire to create dynamic, engaging experiences around characters and situations with the practical considerations of the cost of producing content. We describe a method for assessing player experience by analyzing player facial expressions following key content events in The Wolf Among Us by Telltale Games. Two metrics, engagement and valence, are extracted for six participants who play the first episode of the game. An analysis of the variance and distribution of responses relative to emotionally charged content events and choices suggests that content is designed around events that serve to anchor player emotions while providing the freedom to respond through emotionally-motivated choice selections and content elicitors.
Publication Date
1-1-2018
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
11318 LNCS
Number of Pages
79-92
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-030-04028-4_6
Copyright Status
Unknown
Socpus ID
85058329279 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85058329279
STARS Citation
Murray, John T.; Robinson, Raquel; Mateas, Michael; and Wardrip-Fruin, Noah, "Comparing Player Responses To Choice-Based Interactive Narratives Using Facial Expression Analysis" (2018). Scopus Export 2015-2019. 10560.
https://stars.library.ucf.edu/scopus2015/10560