SoulChat2.0: Psychological Counselor's Digital Twin Framework
SoulChat2.0 is a framework for constructing the digital twin of psychological counselors, designed to support the development of AI applications in mental health. It includes a data generation module and a modeling module, enabling the creation of personalized counseling models based on limited real-world counseling cases.
Detailed Introduction
SoulChat2.0 is a significant advancement in the field of mental health AI, offering a novel approach to building digital twins of psychological counselors. The framework leverages advanced LLMs to generate high-quality synthetic data that captures the language style and therapeutic techniques of specific counselors. This data is then used to fine-tune models, resulting in AI systems that can provide personalized and effective counseling support.
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American National Mental Health Services Survey
The American National Mental Health Services Survey (N-MHSS) is an annual survey conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA) to collect data on mental health treatment facilities across the United States. The survey provides detailed information on the services and characteristics of these facilities, helping to inform policy and improve mental health care.
Emotional First Aid Raw Dataset: Psychological Counseling QA Raw Corpus
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.
Depression: Twitter Dataset + Feature Extraction
This dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.