rafalposwiata/depression-detection-lt-edi-2022
This repository contains the code of our winning solution for the Shared Task on Detecting Signs of Depression from Social Media Text at LT-EDI-ACL2022.
This project helps mental health researchers or clinicians analyze social media text to identify signs of depression. It takes English social media posts as input and classifies them into 'not depressed', 'moderately depressed', or 'severely depressed' categories. The tool is designed for mental health professionals, social scientists, or researchers studying mental well-being through digital footprints.
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Use this if you need to automatically categorize social media text to gauge depression levels for research or preliminary screening purposes.
Not ideal if you require a diagnostic tool for individual clinical use, as this is for research and preliminary analysis.
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Python
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May 12, 2023
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