A Comparative Study of Machine Learning Models for Stress Detection in Academic Social Media Posts
Year: 2026
Type: article
Abstract: 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.
Author: Tufail, Imama
Institution: Bahria University
Language: English
Topic: Mental Health via Writing
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7136647894
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