How smart does your profile image look? Estimating intelligence from social network profile images
This research addresses the issue of inaccurate stereotyping and privacy concerns in social networks, where profile images are often public by default, but it is incremental as it applies existing methods to a new dataset.
The study tackled the problem of estimating intelligence from Facebook profile images by using automatically extracted image features to predict both measured and perceived intelligence, achieving human-level accuracy in this difficult task.
Profile images on social networks are users' opportunity to present themselves and to affect how others judge them. We examine what Facebook images say about users' perceived and measured intelligence. 1,122 Facebook users completed a matrices intelligence test and shared their current Facebook profile image. Strangers also rated the images for perceived intelligence. We use automatically extracted image features to predict both measured and perceived intelligence. Intelligence estimation from images is a difficult task even for humans, but experimental results show that human accuracy can be equalled using computing methods. We report the image features that predict both measured and perceived intelligence, and highlight misleading features such as "smiling" and "wearing glasses" that are correlated with perceived but not measured intelligence. Our results give insights into inaccurate stereotyping from profile images and also have implications for privacy, especially since in most social networks profile images are public by default.