I aim in this project to analyze the sentiment of tweets provided from the Sentiment140 dataset by developing a machine learning sentiment analysis model involving the use of classifiers. The performance of these classifiers is then evaluated using accuracy and F1 scores.

Comparative study of classification algorithms implemented in PySpark on the Sentiment 140 dataset.

Includes 8 archived sentiment analysis datasets for research (Top Open Source Datasets for Data Science)

This project develops a deep learning model that trains on 1.6 million tweets for sentiment analysis to classify any new tweet as either being positive or negative.

A ML project to analyse the sentiments of tweets from the Sentiment140 dataset with 1.6 million tweets.

Sentiment analysis using deep learning models and FastText embedding on Apache Spark

To classify whether the tweet is depressive or not