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SUMMARY:Big data for gender equality: digital records of gendered interest
 s are associated with state-level gender equality in the US - Youyou Wu
DTSTART:20150609T150000Z
DTEND:20150609T160000Z
UID:TALK59729@talks.cam.ac.uk
CONTACT:Chan Yin Wah Fiona
DESCRIPTION:Gender segregation in interests\, activities\, and lifestyles 
 is a ubiquitous phenomenon: girls like shopping\, makeup\, and Victoria Se
 cret\; guys like games\, sports\, and Iron Maiden. In recent decades\, gen
 dered interests and activities are increasingly promoted by media\, popula
 r culture\, and consumer markets. This trend animates debates about its im
 plications for gender equality\, particularly whether it reinforces gender
  stereotypes and brings disadvantages to women. Combining digital records 
 of interests – Facebook Likes – and machine learning algorithms\, we a
 re able to measure how gender-stereotypical people’s interests are in a 
 given population. We show that such gender segregation in interests is str
 ongly associated with indices of state-level gender inequality in the US. 
 Our research showcases the potential for using big data to advise social p
 olicy related to gender equality. \n
LOCATION:2nd Floor Seminar Room\, Department of Psychology\, Downing Site\
 , Cambridge
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