A statistical analysis for COVID-19 as a contract tracing approach and social network communication management. (20th January 2022)

• Record Type: Journal Article
• Authors: Swain, Anasuya; Satpathy, Suneeta; Dutta, Saibal; Sahoo, Sipra; Hamad, Abdulsattar Abdullah
• Is Part Of: International journal of computer applications technology. Volume 66:Number 3/4(2021)
• Page Start: 279
• Page End: 285
• Publication Date: 2022-01-20
• Subjects: COVID-19 -- infectious -- preventive controls -- awareness -- social media -- contact tracing -- artificial intelligence; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

Abstract

The COVID-19 caused by severe acute respiratory syndrome coronavirus2 (SARS-CoV-2) was first detected in Wuhan city of China and later declared as global pandemic by World Health Organization (WHO). The disease is spread through droplets hung in the air produced from nose and mouth by coughing, sneezing and talking. The preventive measures for this infectious disease can be taken by creating awareness and implementation of the contact tracing process. Contact tracing aims to find infected persons as well as persons who came in contact with infected ones. Social media networking can be adopted as a contact tracing and awareness tool and then data collected from this can be analysed with different classifiers and statistical learning methods of AI. This paper has adopted Natural Language Processing (NLP) method to process social network data followed by validation of the relationship between social networking as contact tracing tool and AI techniques with regression, coefficient correlation and Anova.