Evaluating gender portrayal in Bangladeshi TV

TL;DR

This study uses computer vision techniques to analyze gender representation in Bangladeshi TV, revealing unique disparities and challenging common assumptions about gender and skin tone in media.

Contribution

It introduces a novel application of head pose, gender detection, and skin color estimation to analyze gender portrayal in Bangladeshi television, uncovering unexpected patterns.

Findings

Female presence is lower in advertisements and political shows.

Darker skin tones are more common than lighter ones.

Body language markers do not clearly indicate gender dynamics.

Abstract

Computer Vision and machine learning methods were previously used to reveal screen presence of genders in TV and movies. In this work, using head pose, gender detection, and skin color estimation techniques, we demonstrate that the gender disparity in TV in a South Asian country such as Bangladesh exhibits unique characteristics and is sometimes counter-intuitive to popular perception. We demonstrate a noticeable discrepancy in female screen presence in Bangladeshi TV advertisements and political talk shows. Further, contrary to popular hypotheses, we demonstrate that lighter-toned skin colors are less prevalent than darker complexions, and additionally, quantifiable body language markers do not provide conclusive insights about gender dynamics. Overall, these gender portrayal parameters reveal the different layers of onscreen gender politics and can help direct incentives to address existing disparities in a nuanced and targeted manner.