The Emotional First Aid Dataset is a comprehensive Chinese psychological counseling QA corpus, featuring 20,000 multi-turn dialogues. It is designed to support the development of AI applications in the field of psychological counseling and is available for research purposes.
The Emotional First Aid Dataset is a valuable resource for researchers and developers working on AI-powered psychological counseling tools. It includes detailed multi-turn dialogues, topic labels, and emotional annotations, making it suitable for a variety of tasks such as emotion classification and counseling dialogue generation.
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.
This dataset contains survey responses from individuals in the tech industry about their mental health, including questions about treatment, workplace resources, and attitudes towards discussing mental health in the workplace. By analyzing this dataset, we can better understand how prevalent mental health issues are among those who work in the tech sector—and what kinds of resources they rely upon to find help—so that more can be done to create a healthier working environment for all.
The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) uses epidemiological, behavioral, and neuroimaging data to understand how individuals can best retain cognitive abilities into old age. The Cam-CAN Data Access Portal provides access to datasets from the Cambridge Centre for Ageing and Neuroscience, including neuroimaging and cognitive data from participants aged 18-90.