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Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron.

Authors :
Lande, Janhavi
Pillay, Arti
Chandra, Rohitash
Source :
PLoS ONE; 8/1/2023, Vol. 18 Issue 8, p1-26, 26p
Publication Year :
2023

Abstract

Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as the COVID-19 pandemic. In this paper, we use prominent deep learning-based language models for COVID-19 topic modelling taking into account data from the emergence (Alpha) to the Omicron variant in India. Our results show that the topics extracted for the subsequent waves had certain overlapping themes such as governance, vaccination, and pandemic management while novel issues aroused in political, social and economic situations during the COVID-19 pandemic. We also find a strong correlation between the major topics with news media prevalent during the respective time period. Hence, our framework has the potential to capture major issues arising during different phases of the COVID-19 pandemic which can be extended to other countries and regions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
18
Issue :
8
Database :
Complementary Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
169706020
Full Text :
https://doi.org/10.1371/journal.pone.0288681