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.
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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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Emotional First Aid Dataset: Psychological Counseling QA Corpus
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.
HappyDB: a happiness database of 100,000 happy moments
HappyDB is a crowd-sourced collection of 100,000 happy moments designed to advance the understanding of happiness through text analysis. The database is publicly available and aims to support research in natural language processing (NLP) and positive psychology. It provides insights into the causes of happiness and suggests sustainable actions for improving well-being.
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.