@inproceedings{6b47541ea19c453396d5376ada829aa3,
title = "Knowing me knowing you: Exploring effects of culture and context on perception of robot personality",
abstract = "We carry out a set of experiments to assess collaboration between human users and robots in a cross-cultural setting. This paper describes the study design and deployment of a video-based study to investigate task-dependence and cultural-background dependence of the personality trait attribution on a socially interactive robot. In Human-Robot Interaction, as well as in Human-Agent Interaction research, the attribution of personality traits towards intelligent agents has already been researched intensively in terms of the social similarity or complementary rule. We assume that searching the explanation for personality trait attribution in the similarity and complementary rule does not take into account important contextual factors. Just like people equate certain personality types to certain professions, we expect that people may have certain personality expectations depending on the context of the task the robot carries out. Because professions have different social meaning in different national culture, we also expect that these task-dependent personality preferences differ across cultures. Therefore, wesuggest an experiment that considers the task-context and the cultural-background of users.",
keywords = "HMI-HF: Human Factors, EWI-22985, Task Context, IR-84263, Cultural Differences, Human Robot Interaction, METIS-296443, personality perception",
author = "A. Weiss and {van Dijk}, {Elisabeth M.A.G.} and Vanessa Evers",
note = "http://eprints.ewi.utwente.nl/22985 ; ICIC '12 4th international conference on Intercultural Collaboration ; Conference date: 21-03-2012 Through 23-03-2012",
year = "2012",
month = mar,
doi = "10.1145/2160881.2160903",
language = "Undefined",
isbn = "978-1-4503-0818-2",
publisher = "Association for Computing Machinery",
pages = "133--136",
booktitle = "ICIC '12 Proceedings of the 4th international conference on Intercultural Collaboration",
address = "United States",
}