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Eyes Are Windows to the Chinese Soul: Evidence from the Detection of Real and Fake Smiles

Overview of attention for article published in PLOS ONE, May 2011
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Title
Eyes Are Windows to the Chinese Soul: Evidence from the Detection of Real and Fake Smiles
Published in
PLOS ONE, May 2011
DOI 10.1371/journal.pone.0019903
Pubmed ID
Authors

Xiaoqin Mai, Yue Ge, Lin Tao, Honghong Tang, Chao Liu, Yue-Jia Luo

Abstract

How do people interpret the meaning of a smile? Previous studies with Westerners have found that both the eyes and the mouth are crucial in identifying and interpreting smiles, yet less is known about Easterners. Here we reported that when asking the Chinese to judge the Duchenne and non-Duchenne smiles as either real or fake, their accuracy and sensitivity were negatively correlated with their individualism scores but positively correlated with their collectivism scores. However, such correlations were found only for participants who stated the eyes to be the most useful references, but not for those who favored the mouth. Moreover, participants who favored the eyes were more accurate and sensitive than those who favored the mouth. Our results thus indicate that Chinese who follow the typical Eastern decoding process of using the eyes as diagnostic cues to identify and interpret others' facial expressions and social intentions, are particularly accurate and sensitive, the more they self-report greater collectivistic and lower individualistic values.

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Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Netherlands 1 1%
Italy 1 1%
Germany 1 1%
Finland 1 1%
Australia 1 1%
Spain 1 1%
New Zealand 1 1%
Unknown 68 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 17%
Researcher 11 14%
Student > Master 9 12%
Student > Bachelor 9 12%
Student > Doctoral Student 7 9%
Other 16 21%
Unknown 12 16%
Readers by discipline Count As %
Psychology 34 44%
Medicine and Dentistry 7 9%
Computer Science 6 8%
Social Sciences 4 5%
Agricultural and Biological Sciences 3 4%
Other 12 16%
Unknown 11 14%