id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-315647-isjacgq1	Alanazi, E.	Identifying and Ranking Common COVID-19 Symptoms from Arabic Twitter	2020-06-12		.txt	text/plain	2613	159	61	Objective: The aim of this study is to identify the most common symptoms reported by covid-19 patients in the Arabic language and order the symptoms appearance based on the collected data. For example, Twitter has been the source for data for many health and medical studies; such as surveillance and monitoring of Flu and Cancer timeline and distribution across the USA using Twitter [1] , analyzing the spread of influenza in the UAE based on geotagged Arabic Tweets [2] , surveillance and monitoring of Influenza in the UAE based on Arabic and English tweets [3] , identifying symptoms and disease in Saudi Arabia using Twitter [4] , and most recently on analyzing COVID-19 symptoms on Twitter [5] and analyzing the chronological and geographical distribution of COVID-19 infected tweeters in the USA [6] . Initially, we shuffled Arabic tweets and searching for tweets with COVID-19 symptoms and also collected tweets for users who reported themselves infected through clinical test.	./cache/cord-315647-isjacgq1.txt	./txt/cord-315647-isjacgq1.txt