AI-Driven Mental Health Conversations Dataset

Dataset Features

• Conversation Data:
  • Context: User queries or concerns presented to psychologists.
  • Response: Expert replies crafted by psychologists to address user concerns.
• Size and Format:
  • Two columns: Context and Response.
  • File format: CSV, with structured dialogue data for easy use in NLP applications.

Usage

• NLP Model Development:
  • Train AI systems to generate empathetic and contextually accurate responses for mental health support.
• Psychological Research:
  • Analyze themes in user concerns and expert responses to better understand prevalent mental health issues.
• AI-Based Therapy Tools:
  • Build tools that simulate human-like psychological support for preliminary or supplementary mental health care.
• Text Mining and Sentiment Analysis:
  • Extract key insights and emotional tone from conversations to enhance AI interpretive abilities.

License

• Source: Huggingface Hub.
• License: CC0 1.0 Universal (Public Domain Dedication).

Who Can Use It

• Researchers: For studying conversational patterns and thematic insights in mental health.
• AI Developers: To build AI-powered mental health support systems.
• Mental Health Professionals: Exploring AI’s potential for scalable and accessible care solutions.
• Data Scientists: Working on sentiment analysis, dialogue systems, or text classification projects.

Dataset Details

• License: Public Domain (CC0).
• Data Format: CSV.
• Columns:
  • Context: User’s mental health query or concern.
  • Response: Psychologist’s reply.