Explainable detection of depression in Arabic tweets: identifying clinically meaningful linguistic markers using SHAP

Background

Depression detection models for Arabic social-media text often achieve high predictive accuracy but operate as black boxes, limiting their acceptability in clinical and public-health contexts. This study aimed to develop and evaluate an explainable machine learning framework capable of identifying clinically meaningful linguistic markers of depression in Arabic tweets.