BouzidiImen/Social_media_Prediction_depression
This consists in using a variety of social networks data, including both images and texts, to detect early signs of depression.
This project helps mental health professionals and researchers identify potential early signs of depression by analyzing public social media data. It takes publicly available images from platforms like Pexels and Unsplash, and public tweets from Twitter, then processes them to output indicators related to depression. The tool is for mental health practitioners, researchers, or social scientists interested in leveraging social media for mental health insights.
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Use this if you are a mental health professional or researcher looking to explore how publicly available social media content (images and text) can be analyzed to identify early indicators of depression.
Not ideal if you need a clinical diagnostic tool or a solution for analyzing private patient data, as this project focuses on public social media content for research and early indication.
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12
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6
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Feb 03, 2023
Commits (30d)
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