خلال الأشهر القليلة الماضية، كانت هناك أعداد هائلة من التغريدات المتداولة والمناقشات حول Vironavirus (Covid-19) في المنطقة العربية.من المهم لصانعي السياسات والعديد من الأشخاص تحديد أنواع التغريدات المشتركة لفهم السلوك العام بشكل أفضل، ومواضيع المصالح، وطلبات الحكومات، ومصادر التغريدات، وما إلى ذلك. كما أنه من الأهمية بمكان انتشار شائعات وإضاءة في الفيروس أوعلاجات سيئة.تحقيقا لهذه الغاية، نقدم أكبر مجموعة بيانات مشروحة يدويا من تغريدات عربية تتعلق بالكوف (19).نحن تصف إرشادات التوضيحية، وتحليل DataSet لدينا وبناء نماذج التعلم والتحول في الآلات الفعالة للتصنيف.
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.
References used
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