ISSN: 0973-7510

E-ISSN: 2581-690X

Research Article | Open Access
S.V. Praveen1 , R. Sundar2, Vajratiya Vajrobol3, Rajesh Ittamalla4,
K. Srividya5, Ramadan Abdelmoez Farahat6, Hitesh Chopra7, Mohammad Ebad Ur Rehman8, Chiranjib Chakraborty9 and Kuldeep Dhama10
1XIME Bangalore, Department of Analytics, Hosur Rd, Phase 2, Electronic City, Bengaluru, Karnataka, India.
2Department of IT Systems and Analytics, Indian Institute of Management Jammu, Jammu and Kashmir, India.
3Institute of Informatics and Communication, University of Delhi, Delhi, India.
4Indian Institute of Technology, Hyderabad, Department of Management, IITH Road, Near NH-65, Sangareddy, Kandi, Telangana, India.
5National Institute of Technology, Chemical Engineering department, Tanjore Main Road, NH67, near BHEL, Tiruchirappalli, Tamil Nadu, India.
6Faculty of Medicine, Kafrelsheikh University, Kafrelsheikh, 33511, Egypt.
7Chitkara College of Pharmacy, Chitkara University, Punjab, India.
8Department of Medicine, Rawalpindi Medical University, Rawalpindi – 46000, Pakistan.
9Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata – 700126, West Bengal, India.
10Division of Pathology, ICAR-Indian Veterinary Research Institute, Bareilly, Izatnagar, Uttar Pradesh, India.
Article Number: 8478 | © The Author(s). 2023
J Pure Appl Microbiol. 2023;17(1):567-575.
Received: 03 February 2023 | Accepted: 26 February 2023 | Published online: 03 March 2023
Issue online: March 2023

Individuals with comorbidities (i.e., Diabetes Mellitus, hypertension, heart diseases) are more likely to develop a more severe form of coronavirus disease 2019 (COVID-19), thus, they should take necessary precautions to avoid infection with severe acute respiratory syndrome coronavirus–2 (SARS-CoV-2) and its emerging variants and subvariants by getting COVID-19 vaccination and booster doses. In this regard, we used text analytics techniques, specifically Natural Language Processing (NLP), to understand the perception of Twitter users having comorbidities (diabetes, hypertension, and heart diseases) towards the COVID-19 vaccine booster doses. Understanding and identifying Twitter users’ perceptions and perspectives will help the members of medical fraternities, governments, and policymakers to frame and implement a suitable public health policy for promoting the uptake of booster shots by such vulnerable people. A total of 176,540 tweets were identified through the scrapping process to understand the perception of individuals with the mentioned comorbidities regarding the COVID-19 booster dose. From sentiment analysis, it was revealed that 57.6% out of 176,540 tweets expressed negative sentiments about the COVID-19 vaccine booster doses. The reasons for negative expressions have been found using the topic modeling approach (i.e., risk factors, fear of myocardial fibrosis, stroke, or death, and using vaccines as bio-weapons). Of note, enhancing the COVID-19 vaccination drive by administering its booster doses to more and more people is of paramount importance for rendering higher protective immunity under the current threats of recently emerging newer Omicron subvariants which are presently causing a rise in cases in a few countries, such as China and others, and might lead to a feasible new wave of the pandemic with the surge in cases at the global level.


Booster Dose, COVID-19, Vaccine, Natural Language Processing, Text Analytics

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© The Author(s) 2023. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License which permits unrestricted use, sharing, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.