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 study surveys the attitudes and behaviors of US higher education faculty members regarding online resources, the library, and related topics. It covers a wide range of issues, including faculty dependence on electronic scholarly resources, the transition from print to electronic journals, publishing preferences, e-books, and the preservation of scholarly journals.
This project implements the conversion algorithm from the ToMi dataset to the T4D (Thinking is for Doing) dataset, as introduced in the paper https://arxiv.org/abs/2310.03051. It filters examples with Theory of Mind (ToM) questions and adapts the algorithm to account for second-order false beliefs.
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.