CYMLNov 14, 2017

Evaluating gender portrayal in Bangladeshi TV

arXiv:1711.09728v14 citations
Originality Synthesis-oriented
AI Analysis

This work addresses gender disparities in media representation for a South Asian context, providing nuanced insights to guide targeted interventions.

The study analyzed gender portrayal in Bangladeshi TV using computer vision techniques, finding a noticeable discrepancy in female screen presence in advertisements and political talk shows, with lighter-toned skin colors being less prevalent than darker complexions.

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.

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