halolimat/Social-media-Depression-Detector
:pensive: :disappointed: :persevere: :confounded: :weary: Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"
This tool helps mental health researchers and public health professionals analyze social media data to identify potential indicators of depressive symptoms. You input social media posts and it outputs classifications indicating the likelihood of depressive language. It's designed for those monitoring population-level mental health trends.
No commits in the last 6 months.
Use this if you are a mental health researcher or public health official looking to analyze social media content for signs of depression.
Not ideal if you are a clinician seeking to diagnose or treat individual patients based on their social media posts.
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69
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36
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Feb 26, 2019
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0
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