Conducted research on depression prediction in Twitter data using sentiment analysis and multiple classification algorithms, including Decision Tree, Random Forest Classifier, KNN Classifier, and Naïve Bayes to compare their effectiveness in predicting depression.
Employed TextBlob library for sentiment analysis, and Natural Language Processing techniques, to analyze a dataset of 20,000 English tweets collected via the Twitter API and Kaggle.