An evolving list of electronic media datasets used to model mental health status. This repository curates a variety of datasets from different sources, including social media platforms, online forums, and academic studies, to support research in mental health modeling and AI applications.
The Mental Health Datasets repository is a curated list of datasets that can be used to model and analyze mental health status. It includes datasets from various sources such as Reddit, Twitter, and online support forums, covering a wide range of mental health conditions like depression, anxiety, and suicidal ideation. This resource is invaluable for researchers and developers working on AI models for mental health support and intervention.For an overview of existing datasets, please consider reading the paper 'On the State of Social Media Data for Mental Health Research'.
The Weibo User Depression Detection Dataset is a large-scale dataset for detecting depression in Weibo users. It includes user profiles, tweets, and labels indicating whether the user is depressed. The dataset is useful for researchers working on mental health and social media analysis.
Lingxin (SoulChat) is a psychological health large model fine-tuned with millions of Chinese long-text instructions and multi-turn empathetic dialogue data in the field of psychological counseling.
HeartLink is an empathetic psychological model that uses a large language model fine-tuned on a large empathetic Q&A dataset. It can perceive users' emotions and experiences during conversations and provide empathetic responses using rich psychological knowledge, aiming to understand, comfort, and support users. The responses include emoji expressions to bridge the gap with users, offering psychological support and help during consultations.