{"ID":2831800,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.07797","arxiv_id":"2512.07797","title":"LLM Use for Mental Health: Crowdsourcing Users' Sentiment-based Perspectives and Values from Social Discussions","abstract":"Large language models (LLMs) chatbots like ChatGPT are increasingly used for mental health support. They offer accessible, therapeutic support but also raise concerns about misinformation, over-reliance, and risks in high-stakes contexts of mental health. We crowdsource large-scale users' posts from six major social media platforms to examine how people discuss their interactions with LLM chatbots across different mental health conditions. Through an LLM-assisted pipeline grounded in Value-Sensitive Design (VSD), we mapped the relationships across user-reported sentiments, mental health conditions, perspectives, and values. Our results reveal that the use of LLM chatbots is condition-specific. Users with neurodivergent conditions (e.g., ADHD, ASD) report strong positive sentiments and instrumental or appraisal support, whereas higher-risk disorders (e.g., schizophrenia, bipolar disorder) show more negative sentiments. We further uncover how user perspectives co-occur with underlying values, such as identity, autonomy, and privacy. Finally, we discuss shifting from \"one-size-fits-all\" chatbot design toward condition-specific, value-sensitive LLM design.","short_abstract":"Large language models (LLMs) chatbots like ChatGPT are increasingly used for mental health support. They offer accessible, therapeutic support but also raise concerns about misinformation, over-reliance, and risks in high-stakes contexts of mental health. We crowdsource large-scale users' posts from six major social me...","url_abs":"https://arxiv.org/abs/2512.07797","url_pdf":"https://arxiv.org/pdf/2512.07797v1","authors":"[\"Lingyao Li\",\"Xiaoshan Huang\",\"Renkai Ma\",\"Ben Zefeng Zhang\",\"Haolun Wu\",\"Fan Yang\",\"Chen Chen\"]","published":"2025-12-08T18:29:06Z","proceeding":"cs.CY","tasks":"[\"cs.CY\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}