Comparative analysis evaluates machine learning models for stress detection in social media text, suggesting effective approaches.
This study evaluates machine learning approaches for stress detection in academic social media text using the Dreaddit dataset. Five classifiers were assessed across multiple feature configurations. A weighted ensemble with VADER sentiment features achieved 77.90% accuracy and 79.48% F1-Score on 715 test posts.
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Imama Tufail (2026) studied this question.
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