Suicide and Depression Detection

[sreevidya-16]

Is your feature request related to a problem? Please describe.

• The problem of suicide and depression detection involves developing systems or algorithms that can identify individuals at risk of suicide or suffering from depression based on various indicators.
• These indicators can include behavioral patterns, language used in communication (such as social media posts or text messages), physiological signals, and other relevant data points.
• The goal is to create tools that can accurately assess the mental health status of individuals, provide timely interventions or support, and potentially prevent self-harm or suicide attempts.
• This area of research and development typically involves interdisciplinary approaches, combining fields such as psychology, psychiatry, data science, and machine learning to create effective detection and intervention strategies.

Describe the solution you'd like along with reference dataset.

The dataset is a collection of posts from the "SuicideWatch" and "depression" subreddits on the Reddit platform. The posts were collected using the Pushshift API, covering all posts made to "SuicideWatch" from December 16, 2008 (creation) to January 2, 2021, and "depression" posts from January 1, 2009, to January 2, 2021. All posts from "SuicideWatch" are labeled as suicide, while posts from the depression subreddit are labeled as depression. Non-suicide posts were collected from the "teenagers" subreddit.

The dataset used in this project is: https://www.kaggle.com/datasets/nikhileswarkomati/suicide-watch/data

Code of Conduct

• I agree to follow this project's Code of Conduct

[github-actions]

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[github-actions]

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