Understanding the perception of COVID-19 policies by mining a multilanguage Twitter dataset

Understand

The objective of this work is to explore popular discourse about the COVID-19 pandemic and policies implemented to manage it.

• Using Natural Language Processing, Text Mining, and Network Analysis to analyze corpus of tweets that relate to the COVID-19 pandemic, we identify common responses to the pandemic and how these responses differ across time.
• Moreover, insights as to how information and misinformation were transmitted via Twitter, starting at the early stages of this pandemic, are presented.
• Finally, this work introduces a dataset of tweets collected from all over the world, in multiple languages, dating back to January 22nd, when the total cases of reported COVID-19 were below 600 worldwide.