Verbal anthropomorphism design of social robots: Investigating users’ privacy perception

Hanna Chung, Hyunmin Kang, Soojin Jun

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Many studies on the anthropomorphism of social robots have revealed two aspects of anthropomorphism in human–robot interaction. The first is that humanlike robots have advantages of emotional, functional, and relational interaction with users, and the second is that they have disadvantages of privacy perception. Some researchers have claimed that there would be an optimal anthropomorphism of social robots balancing the two aspects. In this study, we explore the optimal level of verbal anthropomorphism of social robots through privacy perception. We designed social robots’ verbal anthropomorphism with various verbal style cues and conducted two studies related to physical and informational privacy based on three levels of verbal anthropomorphism: high, medium, and low. The results revealed that a medium-level verbal anthropomorphism was preferred by participants in terms of privacy perception, whereas they preferred a high-level verbal anthropomorphism in terms of emotional, functional, and relational aspects. This implies that the optimal level of verbal anthropomorphism of social robots may vary depending on privacy perceptions. Based on these findings, we propose adaptable verbal anthropomorphism design of social robots depending on conversation contexts. This paper offers directions to researchers and practitioners who want to design the verbal anthropomorphism of social robots.

Original languageEnglish
Article number107640
JournalComputers in Human Behavior
Volume142
DOIs
Publication statusPublished - 2023 May

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Arts and Humanities (miscellaneous)
  • Human-Computer Interaction
  • General Psychology

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