Mental-Health-Corpus-github

Mental-Health-Corpus-github

The Mental Health Corpus contains labeled comments on mental health issues, used for sentiment and toxic language analysis.

Mental-Health-Corpus-github

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The Mental Health Corpus contains tagged comments about mental health issues for sentiment and toxic language analysis.

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Emotional First Aid Raw Dataset: Psychological Counseling QA Raw Corpus
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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.

Mental Health in Tech Survey
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Mental Health in Tech Survey

This dataset contains survey responses from individuals in the tech industry about their mental health, including questions about treatment, workplace resources, and attitudes towards discussing mental health in the workplace. By analyzing this dataset, we can better understand how prevalent mental health issues are among those who work in the tech sector—and what kinds of resources they rely upon to find help—so that more can be done to create a healthier working environment for all.

IC-AnnoMI: In-Context MI Dialogues - GitHub Repository
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IC-AnnoMI: In-Context MI Dialogues - GitHub Repository

The IC-AnnoMI repository contains source code and a synthetic dataset generated through in-context zero-shot LLM prompting for mental health and therapeutic counselling. IC-AnnoMI is a project that generates contextual MI dialogues using large language models (LLMs). The project contains source code and a synthetic dataset generated through zero-shot prompts, aiming to address the data scarcity and inherent bias problems in mental health and therapeutic consultation.

Anahtar Kelimeler

Collaborative AssessmentMental IllnessSystematic ReviewDatasetFigshare

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