  This paper focuses on Sentiment Analysis of Covid-19 related messages from
the r/Canada and r/Unitedkingdom subreddits of Reddit. We apply manual
annotation and three Machine Learning algorithms to analyze sentiments conveyed
in those messages. We use VADER and TextBlob to label messages for Machine
Learning experiments. Our results show that removal of shortest and longest
messages improves VADER and TextBlob agreement on positive sentiments and
F-score of sentiment classification by all the three algorithms
