Covid-19 Vaccination: An Attitude Analysis of Global Users of Social Media Towards Government Communication
| Published date | 01 June 2024 |
| DOI | http://doi.org/10.1177/00195561231221805 |
| Author | Ajay Kumar Singh,Aditya P. Tripathi,Priti Jagwani,Noopur Agrawal |
| Date | 01 June 2024 |
Covid-19 Vaccination:
An Attitude Analysis of
Global Users of Social
Media Towards
Government
Communication
Ajay Kumar Singh1, Aditya P. Tripathi2, Priti Jagwani3 and
Noopur Agrawal4
Abstract
Amidst a global pandemic, the key challenge before governments, health institu-
tions and administrative authorities is to communicate and inform the general pub-
lic about the never-heard of morbidity, virology and immunity in their simplest
form and language. However, this can only be possible when they can appropriately
predict the perceptions and reactions of public to a given set of communications
regarding the disease, preventive measures and the adoption of established prin-
ciples of users’ perceptions. This article is a study of the users’ perceptions about
Covid-19 vaccination. It conducts sentiment analysis in Python on a dataset of
global users of the social media channel Twitter. The dataset available at kaggle.
com, comprising 51,393 tweets from December 2020 to February 2021 with more
than fifteen features, was put to test. The majority of the people (60.8%) expressed
their neutral sentiments towards vaccination, while 23.9% had a positive opinion.
Further, in order to evaluate the aforementioned analysis, the machine learning
pipeline process of model evaluation is also performed. This process includes a
split of dataset into training and testing, followed by determining various evaluation
parameters including confusion matrix, precision, recall and F1-score. The accu-
racy of 97.1% depicts the outperformance of the model.
Keywords
Covid-19 vaccination, global pandemic, users’ perceptions, government commu-
nication, outperformance of the model
Article
Indian Journal of Public
Administration
70(2) 318–331, 2024
© 2024 IIPA
Article reuse guidelines:
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DOI: 10.1177/00195561231221805
journals.sagepub.com/home/ipa
1 Department of Commerce, Faculty of Commerce & Business, Delhi School of Economics, Univer-
sity of Delhi, Delhi, India
2 Department of Commerce, Shyam Lal College (Evening), University of Delhi, Delhi, India
3 Department of Computer Science, Arya Bhatta College, University of Delhi, New Delhi, India
4 Department of Commerce, Shaheed Bhagat Singh College, University of Delhi, New Delhi, India
Corresponding author:
Aditya P. Tripathi, Department of Commerce, Shyam Lal College (Evening), University of Delhi, Delhi
110032, India.
E-mail: aptripathi@shyamlale.du.ac.in
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