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Minimal Social Cues, Body Proportion, Head Shape, and Participant's Gender on the Trustworthiness of Social Robots.

Authors :
Jia, Xiaoyu
Chen, Chien-Hsiung
Source :
International Journal of Human-Computer Interaction. Dec2024, Vol. 40 Issue 23, p8328-8339. 12p.
Publication Year :
2024

Abstract

Exploring and validating factors that may influence the trustworthiness of social robots is of great significance to improving the effect of human-robot interaction. The purpose of this study was to explore the impact of several design factors on people's perceptions of the trustworthiness of social robots. The research variables were social cues (ie, watching-eyes configuration, control configuration, and neutral configuration), head shape (ie, round head and rectangular head), body proportion (ie, low body proportion and high body proportion), and participant's gender (ie, male and female). Twelve static synthetic social robots were created and presented to the participants as digital pictures. A total of 175 participants took part in the experiment through the online survey via the convenience sampling method. The generated results were as follows: (1) The robots with round heads appear to be more trustworthy than those with rectangular heads. (2) Robots with high body proportion are considered to be more trustworthy than robots with low body proportion. (3) Minimal social cues and body proportion of robots also have a significant interaction effect on improving the trustworthiness of robots. In the watching-eyes configuration, high body proportion is considered more trustworthy than low body proportion. On one hand, the results of this study can provide a good reference for the appearance form of social robots in human-robot interaction to serve human beings, and on the other hand, it also lays a foundation for further exploring the influence of social cues elicited by a series of social robot appearances and social behaviors regarding the trustworthiness of social robots. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10447318
Volume :
40
Issue :
23
Database :
Academic Search Index
Journal :
International Journal of Human-Computer Interaction
Publication Type :
Academic Journal
Accession number :
181197863
Full Text :
https://doi.org/10.1080/10447318.2023.2279418