{"ID":2879802,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.15440","arxiv_id":"2508.15440","title":"M-HELP: Using Social Media Data to Detect Mental Health Help-Seeking Signals","abstract":"Mental health disorders are a global crisis. While various datasets exist for detecting such disorders, there remains a critical gap in identifying individuals actively seeking help. This paper introduces a novel dataset, M-Help, specifically designed to detect help-seeking behavior on social media. The dataset goes beyond traditional labels by identifying not only help-seeking activity but also specific mental health disorders and their underlying causes, such as relationship challenges or financial stressors. AI models trained on M-Help can address three key tasks: identifying help-seekers, diagnosing mental health conditions, and uncovering the root causes of issues.","short_abstract":"Mental health disorders are a global crisis. While various datasets exist for detecting such disorders, there remains a critical gap in identifying individuals actively seeking help. This paper introduces a novel dataset, M-Help, specifically designed to detect help-seeking behavior on social media. The dataset goes be...","url_abs":"https://arxiv.org/abs/2508.15440","url_pdf":"https://arxiv.org/pdf/2508.15440v1","authors":"[\"MSVPJ Sathvik\",\"Zuhair Hasan Shaik\",\"Vivek Gupta\"]","published":"2025-08-21T11:02:36Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[]","has_code":false}