The Robotic Social Attributes Scale (RoSAS): Development and Validation
Abstract
Accurately measuring perceptions of robots has become increasingly important as technological progress permits more frequent and extensive interaction between people and robots. Across four studies, we develop and validate a scale to measure social perception of robots. Drawing from the Godspeed Scale and from the psychological literature on social perception, we develop an 18-item scale (The Robotic Social Attribute Scale; RoSAS) to measure people's judgments of the social attributes of robots. Factor analyses reveal three underlying scale dimensions-warmth, competence, and discomfort. We then validate the RoSAS and show that the discomfort dimension does not reflect a concern with unfamiliarity. Using images of robots that systematically vary in their machineness and gender-typicality, we show that the application of these social attributes to robots varies based on their appearance.
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The Robotic Social Attributes Scale includes warmth, competence, and discomfort as measures of the social perception of robots.
“such as the Robotic Social Attributes Scale (Carpinella et al., 2017) which includes warmth, competence, and discomfort as measures of the social perception of robots.”
From Development and Validation of a Basic Psychological Needs Scale for Technology Use (2024) · cites this paper as Carpinella et al., 2017
Cites
Universal dimensions of social cognition: warmth and competence
Fiske, S. T., Cuddy, A. J. C., & Glick, P. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.11.005 · Cited by 4,567 · see citing works
On seeing human: A three-factor theory of anthropomorphism
Epley, N., Waytz, A., & Cacioppo, J. T. (2007) · Psychological Review · doi:10.1037/0033-295x.114.4.864 · Cited by 4,069 · cited 1× · see citing works
“, when they have recently been used or when robots appear more humanlike) [10].”
BackgroundMachines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · see citing works
Are Machines Gender Neutral? Gender‐Stereotypic Responses to Computers With Voices
Nass, C., Moon, Y., & Green, N. (1997) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1997.tb00275.x · Cited by 670 · see citing works
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Godspeed Questionnaire Series: Translations and Usage
Bartneck, C. (2023) · International Handbook of Behavioral Health Assessment · doi:10.1007/978-3-030-89738-3_24-1 · Cited by 100 · see citing works
A Systematic Review of Ten Years of Research on Human Interaction with Social Robots
Lambert, A., Norouzi, N., Bruder, G., & Welch, G. (2020) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2020.1801172 · Cited by 89 · see citing works
Review of Quantitative Empirical Evaluations of Technology for People with Visual Impairments
Brulé, E., Tomlinson, B. J., Metatla, O., Jouffrais, C., & Serrano, M. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376749 · Cited by 76 · see citing works
Learning to Prompt in the Classroom to Understand AI Limits: A Pilot Study
Theophilou, E., Koyutürk, C., Yavari, M., Bursic, S., Donabauer, G., Telari, A., Testa, A., Boiano, R., Hernandez-Leo, D., Ruskov, M., et al. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-47546-7_33 · Cited by 58 · see citing works
Development and Validation of a Basic Psychological Needs Scale for Technology Use
Moradbakhti, L., Leichtmann, B., & Mara, M. (2024) · Psychological Test Adaptation and Development · doi:10.1027/2698-1866/a000062 · Cited by 41 · see citing works
Zhang, K., Xie, Y., Chen, D., Ji, Z., & Wang, J. (2025) · BMC Psychology · doi:10.1186/s40359-025-03284-w · Cited by 38 · see citing works
- Authors
- Carpinella, C. M., Wyman, A. B., Perez, M. A., & Stroessner, S. J.
- Affiliations
- Walt Disney (United States) (US)
- Venue
- Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
- Publisher
- ACM
- Published
- 2017-03-06
- Pages
- 254-262
- OpenAlex
- W2591778563
- Cited by
- 569
- References
- 4
- Citations by year
- 2026: 102 · 2025: 96 · 2024: 82 · 2023: 63 · 2022: 64 · 2021: 60 · 2020: 47 · 2019: 36 · 2018: 16 · 2017: 3
- FWCI
- 44.63
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Human-Robot Interaction (HRI) (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- social perception of robots, human-robot interaction, warmth, competence, discomfort, robot appearance, gender typicality, scale development, scale validation
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