Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10312727 | Computers in Human Behavior | 2016 | 8 Pages |
Abstract
Selfies (self-portrait photographs often taken with a camera phone) are popularly used for self-presentation in social media like Facebook and Instagram. These modern user-generated self-portraits have the potential to draw a more versatile picture of the genders instead of reproducing traditional gender stereotypes often presented in mainstream media and advertising. To investigate the degree of gender stereotyping in selfies, a random sample of 500 selfies uploaded on Instagram (50% representing females, 50% males) was drawn and subjected to quantitative content analysis. The degree of gender stereotyping in the selfies was measured using Goffman's (1979) and Kang's (1997) gender display categories (e.g. feminine touch, lying posture, withdrawing gaze, sparse clothing) plus three social media-related categories (kissing pout, muscle presentation, faceless portrayal). Additionally, gender stereotyping in selfies was directly compared to the degree of gender stereotyping in magazine adverts measured in the same way (Döring & Pöschl, 2006). Results reveal that male and female Instagram users' selfies not only reflect traditional gender stereotypes, but are even more stereotypical than magazine adverts.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Nicola Döring, Anne Reif, Sandra Poeschl,