Abstract
Microblogging site Twitter is one of the most crucial tool for expressing and sharing the opinions and views of everyday life events. Many researchers have used tweets made during the COVID-19 pandemic to monitor the opinion of the people towards the coronavirus vaccine, mental health problems, impact of lockdown, etc. However, these works were mostly limited to the first and second waves of the pandemic. In this work, we aim to study the impact of the third wave of the pandemic, which started in December 2021 in India. We accomplished this by collecting tweet data set of two months, i.e., December 2021 and January 2022, discussing COVID-19 and having country code as “IN". We employed the Latent Dirichlet Allocation (LDA) technique for topic modeling and labeled each tweet message with the topic words that best describe it. We also utilized sentiment labels for each tweet and analyzed the distribution of different topics across different sentiment labels. Our in-depth analysis of week-wise data discovered that the two most discussed topics were “precautionary measures" and “vaccine" where people have discussed about its effectiveness and vaccination drive in India. We found that people mostly had neutral sentiments for the former topic (for instance, in week 6, number of negative tweets: 215 vs number of positive tweets: 196) while for the latter, overall sentiment polarity was negative (for instance, in week 8, number of negative tweets: 621 vs number of positive tweets: 209). It reflects peoples’ mistrust in the COVID-19 vaccine. Such kind of study is extremely helpful for public health agencies to understand the major concerns of people and their varied reactions to different issues.
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The datasets analysed during the current study are available in the “COVID19_Tweets_Dataset” repository at https://github.com/lopezbec/COVID19_Tweets_Dataset.
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Vatsa, D., Yadav, A., Singh, P. et al. An Analytical Insight of Discussions and Sentiments of Indians on Omicron-Driven Third Wave of COVID-19. SN COMPUT. SCI. 4, 791 (2023). https://doi.org/10.1007/s42979-023-02269-z
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DOI: https://doi.org/10.1007/s42979-023-02269-z