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.
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 ToM QA Dataset is designed to evaluate question-answering models' ability to reason about beliefs. It includes 3 task types and 4 question types, creating 12 total scenarios. The dataset is inspired by theory-of-mind experiments in developmental psychology and is used to test models' understanding of beliefs and inconsistent states of the world.
The World Health Organization (WHO) provides a comprehensive collection of global health data, including mental health statistics. This resource offers insights into various mental health conditions and their prevalence, helping researchers and policymakers understand and address mental health challenges worldwide.