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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Designing Personalization Cues for Museum Robots: Docent Observation and Controlled Studies.

Heeyoon Yoon1, Min-Gyu Kim1, SunKyoung Kim2

  • 1Human-Robot Interaction Research Center, Korea Institute of Robotics and Technology Convergence, Pohang 37553, Republic of Korea.

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|November 27, 2025
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Summary
This summary is machine-generated.

Social robots can create personalized experiences in museums using immediate cues, not long-term user data. This research identifies specific robot behaviors that enhance visitor engagement and connection during brief interactions.

Keywords:
human–robot interactionknowledge alignmentmemory continuityperceived personalizationpreference inquiryscience museumvisual recognition accuracy

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Area of Science:

  • Human-Computer Interaction
  • Robotics
  • Social Psychology

Background:

  • Public cultural venues like science museums require social robots to engage diverse visitors in short, one-off interactions.
  • Long-term user modeling is impractical in these settings, necessitating alternative personalization strategies.

Purpose of the Study:

  • To identify immediately interpretable behavioral cues for social robots that can evoke personalization without user profiling.
  • To investigate how specific robot behaviors influence user perception of personalization and intelligence.

Main Methods:

  • Observational study of museum docents to identify effective social interaction strategies.
  • Three controlled laboratory studies using video-based and Wizard-of-Oz (WoZ) methods to test robot cues.
  • Examined recognition accuracy, knowledge alignment, preference inquiry, and memory-based continuity.

Main Results:

  • Robot recognition accuracy positively influenced social impressions of intelligence.
  • Knowledge alignment, explicit preference inquiry, and memory-based continuity cues significantly increased perceived personalization.
  • Micro-level personalization cues are effective in short-term encounters.

Conclusions:

  • Social robots can achieve personalization in public venues through interpretable, short-term behavioral cues.
  • Findings support user-centered design for social robots in public environments, enhancing visitor engagement.
  • Effective personalization does not require extensive user data or long-term profiling.