id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-209697-bfc4h4b3	Shanthakumar, Swaroop Gowdra	Analyzing Societal Impact of COVID-19: A Study During the Early Days of the Pandemic	2020-10-27		.txt	text/plain	4411	234	57	We first manually 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 adopt a state-of-the-art semantic role labeling approach to identify the action words and then leverage a LSTM-based dependency parsing model to analyze the context of action words (e.g., verb deal is accompanied by nouns such as anxiety, stress, and crisis). We group the hashtags into six main categories, namely 1) General COVID, 2) Quarantine, 3) School Closures, 4) Panic Buying, 5) Lockdowns, and 6) Frustration and Hope to quantitatively and qualitatively understand the chain of events. We develop a Seeded LDA model to categorize tweets into the five hashtag groups: i) General COVID, ii) School Closures, iii) Panic Buying, iv) Lockdowns, and v) Quarantine by seeding each group with seed words from our analysis in Section III-B.	./cache/cord-209697-bfc4h4b3.txt	./txt/cord-209697-bfc4h4b3.txt