Topic Models for Assessment of Mental Health Issues
by Maxime D. Armstrong, Diego Maupomé, and Marie-Jean Meurs
Published onJun 08, 2021
Topic Models for Assessment of Mental Health Issues
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Abstract
In this paper, we explore topic modeling for the assessment of risk for depression, anorexia and self-harm. Using social media textual content from different datasets, we focus on Latent Dirichlet Allocation models, trained on both specific and combined corpora made from these datasets to perform risk detection. We investigate mental health vocabulary and shared topic modeling performance improvements on user classification.
Creative Commons Attribution 4.0 International License (CC-BY 4.0)