Exploring the Effects of Support Type and Task Difficulty for Virtual Assistants as Social Companions

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Authors: Sei Kang, YunSu Lee, Gun Lee, Hyung-Jeong Yang, Soo-Hyung Kim, Ji-Eun Shin, Seungwon Kim
Cited by: 1
References: 113

Abstract

Virtual assistants (VAs) are increasingly positioned not just as tools, but as potential social companions—capable of offering either emotional or informational support. Yet, how these forms of support should adapt to varying task difficulties and embodiment styles remains underexplored. We conducted two user studies with cognitive and physical tasks to investigate how support type (emotional vs. informational) shapes user perceptions across variations in task difficulty (easy vs. hard) and embodiment (non-embodied vs. embodied). In Study 1, emotional support positively influenced users’ impressions of VA in easy tasks, while informational support was more effective in difficult tasks. In Study 2, participants also preferred emotional support for easy tasks, but differences between support types were less pronounced for difficult tasks. Notably, embodiment exerted no significant influence in either study. These findings underscore the role of context in shaping effective support strategies, offering design insights for VAs as social companions.

Fields of Study & Subjects

Social Robot Interaction and HRI AI in Service Interactions Virtual Reality Applications and Impacts

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–21
Publication date
13 April 2026