Name: ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic
Description: Collected to prevent
  spreading of rumors and misinformation about
  the virus or bad cures
Provider: QCRI
Paper Title: ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic
Tasks: COVID misinformation detection
Venue Name: nan
Authors: Hamdy Mubarak, Sabit Hassan
Abstract: Over the past few months, there were huge numbers of circulating tweets and discussions about Coronavirus (COVID-19) in the Arab region. It is important for policy makers and many people to identify types of shared tweets to better understand public behavior, topics of interest, requests from governments, sources of tweets, etc. It is also crucial to prevent spreading of rumors and misinformation about the virus or bad cures. To this end, we present the largest manually annotated dataset of Arabic tweets related to COVID-19. We describe annotation guidelines, analyze our dataset and build effective machine learning and transformer based models for classification.