id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-252344-5a0sriq9	Saleh, Sameh N.	Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter	2020-08-06		.txt	text/plain	3667	231	51	CONCLUSIONS: Considering the positive sentiment, preponderance of objective tweets, and topics supporting coping mechanisms, we concluded that Twitter users generally supported social distancing in the early stages of their implementation. 18 We hypothesized that performing sentiment, emotion, and content analysis of tweets related to social distancing on Twitter during the COVID-19 pandemic could provide valuable insight into the public's beliefs and opinions on this policy. We used Python's TextBlob library 21 to perform sentiment analysis for all tweets through natural language processing and text analysis to identify and classify emotions (positive, negative, or neutral) and content topics. We analyzed Twitter activity around the 2 most common social distancing trending hashtags at the study time to understand emotions, sentiment polarity, subjectivity, and topics discussed related to this NPI. Performing sentiment, emotion, and content analysis of tweets provided valuable insight into the public's beliefs and opinions on social distancing.	./cache/cord-252344-5a0sriq9.txt	./txt/cord-252344-5a0sriq9.txt