SUBHADIPMAITI-DEV/Depression-Detection-System-Using-Machine-Learning
This project develops a Depression Detection System using Machine Learning on Twitter data. It predicts depression by analyzing tweets with SVM, Logistic Regression, Decision Trees, and NLTK in Python.
This system helps identify potential signs of depression by analyzing text from social media posts, specifically tweets. It takes raw Twitter data as input and uses machine learning to output predictions about the emotional state expressed in the tweets. This tool would be useful for mental health researchers, public health organizations, or social scientists interested in large-scale sentiment analysis related to mental well-being.
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Use this if you need to quickly process large volumes of Twitter data to flag content that may indicate depressive tendencies, aiding in early detection or broader population studies.
Not ideal if you need a clinical diagnostic tool or a system that works with personal, private mental health records.
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MIT
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Jun 07, 2025
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