Title: An empirical study on COVID-19 for social contact tracing on classification perspective
Authors: Mohammad Gouse Galety; Elham Tahsin Yasin; Abdellah Behri Awol; Lubab Talib
Addresses: Department of Information Technology, Catholic University, Erbil, Iraq ' Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Erbil, Iraq ' Department of Information Systems, Werabe University, Werabe, Ethiopia ' Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Erbil, Iraq
Abstract: The COVID-19 is a pandemic and irresistible one without the antibody and cure. This issue needs preventive controls through the creation of awareness and implementation of the contact tracing process. This device has its usage to lessen the infections with the information described at the infectious disease and reduce the spreadsheet of infections and inflamed human beings. In contrast, social media networking is a superb knowledge set of nowadays market coverage of maximum sociology of the planet to see, analyse and interpret. AI has been used to determine the infected COVID-19 and infers the good action and preventive measures to reduce the expansion of COVID-19. The authors have derived the available data with its analysis and contract tracing through the usage of social media datasets.
Keywords: COVID-19; infectious; preventive controls; awareness; social media; contact tracing; artificial intelligence.
International Journal of Computer Applications in Technology, 2021 Vol.66 No.3/4, pp.303 - 308
Received: 13 Aug 2020
Accepted: 28 Aug 2020
Published online: 21 Jan 2022 *