malik-hasan / Identifying-depression-with-NLP

Identified trends in Twitter data indicative of depression for early intervention using using various ML models including RNN, Logistic Regression, Naive Bayes as well as statistical methods.

Identifying-depression-with-NLP

Identified trends in Twitter data indicative of depression for early intervention using NLP Sentiment analysis and statistical methods.

• Tested and evaluated performance of various machine learning models on the data including Recurrent Neural Networks, Logistic Regression, Naive Bayes
• Applied statistical methods such as ANOVA in conjunction with prior literature to identify trends indicative of depression
• Various libraries were employed including NLTK and PyTorch