The Emotional First Aid Raw Dataset is a collection of raw, unannotated psychological counseling Q&A data, designed to support research in AI applications for mental health. It contains over 172,000 topics with 2,381,273 messages, totaling 44,514,786 characters, providing a rich source of data for natural language processing and AI development.
This dataset is a valuable resource for researchers and developers working on AI-powered psychological counseling tools. It includes a wide range of topics and detailed messages, making it suitable for tasks such as data preprocessing, model training, and dialogue generation. The data is sourced from public websites and has been anonymized and desensitized for privacy protection.
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.
Dataset Card for Psychology Therapy Dataset : This dataset card aims to provide information about a dataset focused on psychology therapy conversations. Language(s) (NLP): Turkish (tr)
The DAIC-WOZ dataset contains clinical interviews designed to support the diagnosis of psychological distress conditions such as anxiety, depression, and post-traumatic stress disorder. This repository provides code for extracting question-level features from the DAIC-WOZ dataset, which can be used for multimodal analysis of depression levels.