When I was in college we used it to try and try a sentiment analysis model since they are notoriously bad at detecting sarcasm and Twitter was full of sarcasm.

When I was in college we used it to try and try a sentiment analysis model since they are notoriously bad at detecting sarcasm and Twitter was full of sarcasm. We also used the API to try and determine the most impacted areas after a natural disaster. Basically it would use the model we trained to try and read tweets of people that needed help or people tweeting about severe damage and group them by their coordinates. The first one I agree isn’t really positive since it is just using other people’s data to train a model, but the second one could’ve been a useful tool to help EMS during a natural disaster.