GitHub - masaki9/COVID-19-Tweets: COVID-19 Vaccine Tweets Sentiment Analysis

I developed classification models that classify COVID-19 vaccine-related tweets into three sentiment classes, positive, neutral, and negative, using scikit-learn. The models classified the sentiments of the tweets with 69% accuracy for Canada and 84% accuracy for the world.
I applied NLP techniques such as lemmatization to extract vaccine-related tweets using NLTK.
I extracted and analyzed n-grams related to vaccines from vaccine-related tweets.
Canada and worldwide data show more positive and neutral sentiments toward COVID-19 vaccines.

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