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Eye Movements to Natural Images as a Function of Sex and Personality

Overview of attention for article published in PLOS ONE, November 2012
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Title
Eye Movements to Natural Images as a Function of Sex and Personality
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0047870
Pubmed ID
Authors

Felix Joseph Mercer Moss, Roland Baddeley, Nishan Canagarajah

Abstract

Women and men are different. As humans are highly visual animals, these differences should be reflected in the pattern of eye movements they make when interacting with the world. We examined fixation distributions of 52 women and men while viewing 80 natural images and found systematic differences in their spatial and temporal characteristics. The most striking of these was that women looked away and usually below many objects of interest, particularly when rating images in terms of their potency. We also found reliable differences correlated with the images' semantic content, the observers' personality, and how the images were semantically evaluated. Information theoretic techniques showed that many of these differences increased with viewing time. These effects were not small: the fixations to a single action or romance film image allow the classification of the sex of an observer with 64% accuracy. While men and women may live in the same environment, what they see in this environment is reliably different. Our findings have important implications for both past and future eye movement research while confirming the significant role individual differences play in visual attention.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Poland 2 2%
Romania 1 <1%
Luxembourg 1 <1%
Germany 1 <1%
Unknown 117 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 23%
Student > Master 21 17%
Researcher 17 14%
Other 11 9%
Professor > Associate Professor 6 5%
Other 19 15%
Unknown 22 18%
Readers by discipline Count As %
Psychology 35 28%
Computer Science 17 14%
Agricultural and Biological Sciences 10 8%
Medicine and Dentistry 7 6%
Neuroscience 7 6%
Other 24 19%
Unknown 24 19%