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