Comparing the Behaviour of Two Topic-Modelling Algorithms in COVID-19 Vaccination Tweets

Coronavirus is a newly developed infectious disease that has triggered a pandemic due to its ease of transmission as of early 2020. Several groups from various countries have been working on a vaccine to prevent and avoid the spread of the virus in this outbreak. In this article, the main objective is to compare LDA against LSA to gain a better understanding of the Tweets and which Topic Modelling technique fits best for this task, additionally if the feedback of the Tweets were positive or negative sentiment. It was concluded that LDA was a better-unsupervised technique for categorizing the raw text in 12 topics.