Title
Leveraging Social Judgment Theory To Examine The Relationship Between Social Cues And Signals In Human-Robot Interactions
Abstract
Human-robot interaction (HRI) research requires new techniques for understanding the social dynamics that occur at the interface between humans and robots. Prior work has focused on incorporating the social cues and social signals distinction from the field of social signal processing and complementing this with recent advances in understanding human social cognition that specify two primary types of cognitive processes. A related account, stemming from Social Judgment Theory (SJT), specifies a Lens Model for which cues can be interpreted as well as the task conditions that would induce either of the types of cognitive processes. Surprisingly, SJT-based research has not yet examined the social cue and signal relationship. We argue it provides an ideal path forward for such research and we integrate these related disciplines of study to provide a theoretically derived account that can be useful for both the design of humanhuman and HRI experiments focused on social interaction dynamics.
Publication Date
1-1-2014
Publication Title
Proceedings of the Human Factors and Ergonomics Society
Volume
2014-January
Number of Pages
1336-1340
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1177/1541931214581279
Copyright Status
Unknown
Socpus ID
84920585784 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84920585784
STARS Citation
Wiltshire, Travis J.; Snow, Sierra L.; Lobato, Emilio J.C.; and Fiore, Stephen M., "Leveraging Social Judgment Theory To Examine The Relationship Between Social Cues And Signals In Human-Robot Interactions" (2014). Scopus Export 2010-2014. 9153.
https://stars.library.ucf.edu/scopus2010/9153