SocialStools
Interacting with strangers can be beneficial but also challenging. Fortunately, these challenges can lead to design opportunities. In this paper, we present the design and evaluation of a socio-spatial interface, SocialStools, that leverages the human propensity for embodied interaction to foster togetherness between strangers. SocialStools is an installation of three responsive stools on caster wheels that generate sound and imagery in the near environment as three strangers sit on them, move them, and rotate them relative to each other.
The three socio-physical affordances of SocialStools: (a) Sitting on the stools; (b) Distance between stools; (c) Angular orientation between stools.
Interaction A: Visualization of Personal Space: Ripples
Interaction B: The distance between people: Sound
Interaction C: The orientation of people: Bubbles
Publications (Ongoing):
Ge Guo, Gilly Leshed, and Keith Evan Green. 2023. “I normally wouldn’t talk with strangers”: Introducing a
Socio-Spatial Interface for Fostering Togetherness Between Strangers. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ‘23), April 23–28, 2023, Hamburg, Germany. ACM, New York, NY, USA 20 Pages. https://doi.org/10.1145/3544548.3581325 🏅Best Paper Honorable Mention (top 5% of submissions)
Ge Guo, Gilly Leshed, Trevor Pinch, and Keith Evan Green. 2022. SocialStools: A Playful, Socio-Spatial Interface for Fostering Togetherness Across Strangers. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (CHI EA ‘22). Association for Computing Machinery, New York, NY, USA, Article 173, 1–5. https://doi.org/10.1145/3491101.3519877
Ge Guo, Hsin-Ming Chao, Huong Pham, Gilly Leshed, and Keith Evan Green. (Minor Revision). Beyond the First Glance: Unraveling Strangers’ Interactions through a Behavioral Framework and Evaluating it in the Field. (Full Paper). The Journal of ACM Transactions on Computer-Human Interaction (TOCHI)
Ge Guo, Qi Yang, Rejoice Hu, and Guy Hoffman. Facilitating Synchronized Movement during Ice-Breaking Scenarios through a Real-World Reinforcement Learning Agent Using Non-Verbal Behaviors. In Extended Abstracts of the 2025 ACM/IEEE International Conference on Human-Robot Interaction Late-Breaking Report, HRI EA’25)