Abstract
This is an exploratory research with a quantitative approach which purpose is observing the levels of sentiment polarity of Twitter users during social isolation. The R Language was used toapply the Text Mining and Sentiment Analysis in a corpus that, treated and structured, was built by tweets associated with the COVID-19 theme. The results obtained reveal that, globally, the people manifested a more positive rather than negative feeling towards their daily routine in the mentioned social media platform.
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