id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-034814-flp6s0wd	Lamsal, Rabindra	Design and analysis of a large-scale COVID-19 tweets dataset	2020-11-06		.txt	text/plain	5515	341	58	This paper presents COV19Tweets Dataset (Lamsal 2020a), a large-scale Twitter dataset with more than 310 million COVID-19 specific English language tweets and their sentiment scores. The amount of data can range from hundreds This article belongs to the Topical Collection: Artificial Intelligence Applications for COVID-19, Detection, Control, Prediction, and Diagnosis Rabindra Lamsal rabindralamsal@outlook.com 1 be (i) trimmed [38] or summarized [36, 40, 41, 50] and sent to the relevant department for further analysis, (ii) used for sketching alert-level heat maps based on the location information contained within the tweet metadata or the tweet body. A study [1] analyzed 2.8 million COVID-19 specific tweets collected between February 2, 2020, and March 15, 2020, using frequencies of unigrams and bigrams, and performed sentiment analysis and topic modeling to identify Twitter users' interaction rate per topic. Multiple studies have performed social network analysis on Twitter data related to the COVID-19 pandemic.	./cache/cord-034814-flp6s0wd.txt	./txt/cord-034814-flp6s0wd.txt