/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.

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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