Today we take a year’s worth of Trump tweets and look at the sentiment behind them. If you are wondering what sentiment analysis is: it is an analysis of text which produces a number quantifying whether the text is conveying a positive or negative emotion.

The video with the easy-to-follow process is available here: Trump tweet sentiment and visualization.

In the video we go over how to use machine learning for text analysis, without writing any code. We also go over some popular machine learning visualizations such as: heat maps and word clouds. Don’t worry about acquiring data for this video, we go over that too!

Sentiment analysis has many applications in consumer applications such as: escalating priority in case management systems, gauging popularity and responses to brands/products/topics, it is also used in stock trading systems.

This process can be re-applied to any collection of text documents! Let me know what you think in the comments below (or on the video).