Context During the 2020 COVID-19 pandemic, social media exploded with content discussing the pandemic and other related issues, tweets discussing this topic was collected from Twitter to build better insights on how the state of the pandemic correlated with people's opinions Content The dataset consists of multiple features obtained from Twitter using a web crawler build with Python and Scrapy, we queried tweets with specific keywords related to the pandemic in the United States from the beginning of February to the end of April of 2020. Alongside our other features such as mentions, hashtags were extracted from the original tweet. Inspiration How could we correlate the state of the pandemic through the specified timeline with people's thoughts on social media?