论文标题
Arcorona：分析冠状病毒早期的阿拉伯推文（Covid-19）大流行
ArCorona: Analyzing Arabic Tweets in the Early Days of Coronavirus (COVID-19) Pandemic
论文作者
论文摘要
在过去的几个月中，阿拉伯地区有大量有关冠状病毒（Covid-19）的循环推文和讨论。对于决策者和许多人来说，重要的是要确定共享推文的类型，以更好地了解公共行为，感兴趣的话题，政府的要求，推文来源等。这对于防止谣言传播和对病毒或不良治疗的误解也至关重要。为此，我们介绍了与Covid-19有关的阿拉伯语推文的最大手动注释数据集。我们描述注释指南，分析我们的数据集并构建有效的机器学习和基于变压器的模型进行分类。
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.
