Description
During the ongoing outbreak of coronavirus disease (COVID-19), people use social media to acquire and exchange various types of information. Therefore, It is important to identify such situational information and to understand how it is being propagated on social media. Our Proposed method to fill this gap by harnessing twitter data and natural language processing techniques to classify the COVID-19-related information into three types of situational information.
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