Twitter Sentiment Analysis using Classical Machine Learning Algorithms

A sentiment categorization system for tweets is designed using classical machine learning algorithms (no deep learning). The dataset comprises of 1.6M tweets (available here) automatically labeled, and thus, noisy. This is part of Natural Language Processing course taken by Prof Mausam.

The model uses ensemble learning approach. An ensemble of 5 classifiers are designed for the prediction task at hand.

Running Mode

Training

bash run-train.sh <data_directory> <model_directory>

Testing

bash run-test.sh <model_directory> <input_file_path> <output_file_path>