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From the moment the first COVID-19 vaccines are rolled out, there will need to be a large fraction of the global population ready in line. It is therefore crucial to start managing the growing global hesitancy to any such COVID-19 vaccine. The current approach of trying to convince the nos cannot work quickly enough, nor can the current policy of trying to find, remove and/or rebut all the individual pieces of COVID and vaccine misinformation. Instead, we show how this can be done in a simpler way by moving away from chasing misinformation content and focusing instead on managing the yes--no--not-sure hesitancy ecosystem.
Using the official data and aware of the uncertain source and insufficient number of samples, we present a first and (for the moment) unique attempt to study the first two months spread of COVID-19 in Madagascar. The approach has been tested by predi
We show that malicious COVID-19 content, including hate speech, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond the control of any individual social media platform. Machine learning topic analysis s
Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical m
Early analyses revealed that dark web marketplaces (DWMs) started offering COVID-19 related products (e.g., masks and COVID-19 tests) as soon as the current pandemic started, when these goods were in shortage in the traditional economy. Here, we broa
As the COVID-19 pandemic continues to ravage the world, it is of critical significance to provide a timely risk prediction of the COVID-19 in multi-level. To implement it and evaluate the public health policies, we develop a framework with machine le