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Global Knowledge, Memory and Communication, 3(71), p. 140-154, 2021

DOI: 10.1108/gkmc-01-2021-0006

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Analysis and visualization of COVID-19 discourse on Twitter using data science: a case study of the USA, the UK and India

Journal article published in 2021 by Haider Ilyas, Ahmed Anwar, Ussama Yaqub, Zamil Alzamil ORCID, Deniz Appelbaum
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Purpose This paper aims to understand, examine and interpret the main concerns and emotions of the people regarding COVID-19 pandemic in the UK, the USA and India using Data Science measures. Design/methodology/approach This study implements unsupervised and supervised machine learning methods, i.e. topic modeling and sentiment analysis on Twitter data for extracting the topics of discussion and calculating public sentiment. Findings Governments and policymakers remained the focus of public discussion on Twitter during the first three months of the pandemic. Overall, public sentiment toward the pandemic remained neutral except for the USA. Originality/value This paper proposes a Data Science-based approach to better understand the public topics of concern during the COVID-19 pandemic.