XAI for Gender Representation in Media Analysis

Abstract

In many countries, studies have highlighted the under-representation of women in the media. But beyond quantitative imbalance is the question of the qualitative asymmetry of men and women portrayals. How to help the evaluation of content and salient features specific to male and female discourse? We propose in this study to leverage the knowledge acquired by a classification model trained for gender detection on automatic transcripts, to highlight patterns distinctive of male or female speech. Results show the relevance of coupling explainable AI with classifier confidence to compute consistent attributions.