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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

Haider Ilyas (Lahore University of Management Sciences, Lahore, Pakistan)
Ahmed Anwar (Lahore University of Management Sciences, Lahore, Pakistan)
Ussama Yaqub (Lahore University of Management Sciences, Lahore, Pakistan)
Zamil Alzamil (Majmaah University, Al Majma'ah, Saudi Arabia)
Deniz Appelbaum (Montclair State University, Montclair, New Jersey, USA)

Global Knowledge, Memory and Communication

ISSN: 2514-9342

Article publication date: 8 June 2021

Issue publication date: 3 March 2022

368

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.

Keywords

Citation

Ilyas, H., Anwar, A., Yaqub, U., Alzamil, Z. and Appelbaum, D. (2022), "Analysis and visualization of COVID-19 discourse on Twitter using data science: a case study of the USA, the UK and India", Global Knowledge, Memory and Communication, Vol. 71 No. 3, pp. 140-154. https://doi.org/10.1108/GKMC-01-2021-0006

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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