Depression-Detection-System-Using-Machine-Learning and DEPRESSION-DETECTION-USING-TWEETS

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Stars: 24
Forks: 2
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Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 13
Forks:
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
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About Depression-Detection-System-Using-Machine-Learning

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.

mental-health-research social-media-monitoring public-health-informatics sentiment-analysis psychological-screening

About DEPRESSION-DETECTION-USING-TWEETS

Amey-Thakur/DEPRESSION-DETECTION-USING-TWEETS

Machine Learning Project for Depression Detection Using Tweets.

This tool helps mental health professionals or researchers analyze social media posts to identify potential depressive characteristics. You input text from tweets, and the system processes it using advanced natural language understanding to output a prediction about depressive sentiment. It's designed for quick, real-time analysis.

mental-health social-media-analysis sentiment-analysis psychological-screening public-health-research

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