Abstract
The COVID-19 pandemic affected all countries worldwide, causing big changes in people's routines due to public policies for disease spreading control. Among the most impacting measures were social distancing policies and lockdown, leading to an intense discussion by the population. To describe this discussion in Brazil, this research applied data science and natural language methods to analyze posts on Twitter. It processed more than 12.9 million tweets between 2020 and 2021, and the results highlighted the main topics discussed by Brazilian Twitter users, such as the ideological-political component. The approach employed in this research proved to help extract valuable information in massive data mass. DOI: 10.36558/rsc.v12i3.7903
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