A Systematic Validation of the Robotic Social Attributes Scale (RoSAS)

Abstract

The Robotic Social Attributes Scale (RoSAS) is widely used in human-robot interaction research to measure the social perception of robots, including warmth, competence, and discomfort. As previous researchers have found ambiguous support for the RoSAS's three-factor structure, the current study aims to evaluate the proposed structure by conducting a confirmatory factor analysis (CFA) using openly available datasets. The CFA (n = 1107) showed that the three-factor model had a poor model fit. This suggests that the RoSAS's three dimensions might better be used as separate scales instead of measuring a broad concept of social perception. When separating by stimulus type, only stimuli using words and vignettes had an acceptable model fit, indicating that the RoSAS might be more suitable for word/vignette stimuli. We recommend using the RoSAS's individual subscales as separate constructs rather than measuring social attributes in general. This approach also aligns with what most research has already adopted.