Mental Health Dialogues Dataset

10,000 text-based conversations provide a corpus for analyzing mental health discourse. The dataset was created by author LasagnaS and last updated in December 2025. Its content is derived from conversational text, focusing on mental health topics.

Use Cases

• Train language models to recognize mental health-related conversational patterns and sentiment in dialogue text.
• Analyze linguistic features and topic distribution within the 10,000 conversation samples.
• Fine-tune classifiers to detect specific mental health conditions or crisis signals from conversational text.
• Benchmark the performance of generative AI models in producing empathetic, mental health-focused responses.

Strengths

• Contains 10,000 individual conversation samples.
• Dataset is actively maintained, with a recent update in December 2025.

Limitations

• Unknown conversation source and collection method limits reproducibility.
• Lack of demographic or clinical metadata restricts sociodemographic analysis.
• Potential class imbalance or topic bias is unverified without column details.

Provenance

Source

Hugging Face user LasagnaS.

Collection Method

Assembled from conversational text; specific gathering method unknown.

Time Range

null

Freshness

Last updated December 2025.

Geography

Platform tags suggest a US region focus, but specific geography is unknown.