FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data

arXiv:2605.18936v1 Announce Type: new Abstract: Social media text data are often used to train Machine Learning (ML) models to identify users exhibiting high-risk mental health behaviors. However, sharing this sensitive data poses privacy risks and limits the growth of benchmark datasets. We comprehensively evaluate whether privacy-preserving ML techniques can enable safer data sharing while preserving performance. Specifically, we apply federated learning (FL) and Differentially Private FL for two widely-studied mental health prediction tasks: depression detection on X (Twitter) and suicide c

Source: arXiv cs.LG — read the full report at the original publisher.

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