@conference {1524085,
	title = {Understanding the Socio-Economic Disruption in the United States during COVID-19{\textquoteright}s Early Days},
	booktitle = {AI for Social Good Workshop},
	year = {2020},
	abstract = {
	In this paper, we collect and study Twitter communications to understand the socio-economic impact of COVID-19 in the United States during the early days of the pandemic. With infections soaring rapidly, users took to Twitter asking people to self isolate and quarantine themselves. Users also demanded closure of schools, bars, and restaurants as well as lockdown of cities and states. The communications reveal the ensuing panic buying and the unavailability of some essential goods, in particular toilet paper. We also observe users express their frustration in their communications as the virus spread continued. We methodically collect a total of 530,206 tweets by identifying and tracking trending COVID-related hashtags. We then group the hashtags into six main categories, namely 1) General COVID, 2) Quarantine, 3) Panic Buying, 4) School Closures, 5) Lockdowns, and 6) Frustration and Hope, and study the temporal evolution of tweets in these hashtags. We conduct a linguistic analysis of words common to all the hashtag groups and specific to each hashtag group. Our preliminary study presents a succinct and aggregated picture of people{\textquoteright}s response to the pandemic and lays the groundwork for future fine-grained linguistic and behavioral analysis.



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},
	author = {Swaroop Gowdra and Anand Seetharam and Arti Ramesh}
}
