This is part two of a two-part NLP series where we carry out sentiment analysis on COVID-19 vaccine tweets. In this part, we visualise changes in tweet sentiment over time for each vaccine, investigate the relationship between sentiment and vaccination progress in different countries and look at the most common words in positive, neutral and negative tweets.
This is part one of a two-part NLP series where we carry out sentiment analysis on COVID-19 vaccine tweets. In this part we follow the ULMFiT approach with fastai to create a Twitter language model, then use this to fine-tune a tweet sentiment classification model.
After using empirical Bayes estimation to model predicted penalty conversion rate, we take a look at the best and worst penalty takers, investigate Manchester City and Fulham's struggles from spot kicks, and use our new estimate to simulate the Euro 96 penalty shootout.