Abstract
Coronavirus COVID-19 is a global pandemic stated by the World Health Organization (WHO) in 2020. The COVID-19 devastating impact was not only affect human life but also many aspects of it such as social interaction, transportation options, personal saving and expenses, and more. The power of social media data in such world pandemic outbreaks provides an efficient source of tracking, raising awareness, and alerts with potentials infection location. Social networks can fight the pandemic by sharing helpful content and statistics based on demographics features of users around the world. There is an urgent need for such frameworks for tracking helpful content, detecting misleading content, ranking the trusted user content, presenting accurate demographics statistics of the outbreak. In this paper, the real-time tweets of Coronavirus pandemic (COVID-19) analysis will be presented. The proposed framework will be used to track the geographical infections, trends of the content, and the user’s categorization. The framework will include analysis, demographics features, statistical charts, classifying the content of tweets related to its usefulness. The performance of the proposed framework is evaluated based on different measures such as classification accuracy, sensitivity, and specificity. Finally, a set of recommendations will be presented to benefit from the proposed framework with its full potentials as a tool to stand against the COVID-19 spreading.
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Ahmed, K., Abdelghafar, S., Salama, A., Khalifa, N.E.M., Darwish, A., Hassanien, A.E. (2021). Tracking of COVID-19 Geographical Infections on Real-Time Tweets. In: Hassanien, A.E., Darwish, A. (eds) Digital Transformation and Emerging Technologies for Fighting COVID-19 Pandemic: Innovative Approaches. Studies in Systems, Decision and Control, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-63307-3_19
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DOI: https://doi.org/10.1007/978-3-030-63307-3_19
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