Exploring COVID-19 vaccine hesitancy and behavioral themes using social media big-data: a text mining approach

Abstract

Purpose

India has the biggest number of active users on social media platforms, particularly Twitter. The purpose of this paper is to examine public sentiment on COVID-19 vaccines and COVID Appropriate Behaviour (CAB) by text mining (topic modeling) and network analysis supported by thematic modeling.

Design/methodology/approach

A sample dataset of 115,000 tweets from the Twitter platform was used to examine the perception of the COVID-19 vaccination and CAB from January 2021 to August 2021. The research applied a machine-learning algorithm and network analysis to extract hidden and latent patterns in unstructured data to identify the most prevalent themes. The COVID-19 Vaccine Hesitancy Amplification Model was formulated, which included five key topics based on sample big data from social media.

Findings

The identified themes are Social Media Adaptivity, Lack of Knowledge Providing Mechanism, Perception of Vaccine Safety Measures, Health Care Infrastructure Capabilities and Fear of Coronavirus (Coronaphobia). The study implication assists communication strategists and stakeholders design effective communication strategies using digital platforms. The study reveals CAB themes as with Mask Wearing Issues and Employment Issues as relevant themes discussed on digital channels.

Research limitations/implications

The themes extracted in the present study provide a roadmap for policy-makers and communication experts to utilize social media platforms for communicating and understanding the perception of preventive measures of vaccination and CAB. As evidenced by the increased engagement on social media platforms during the COVID-19-induced lockdown, digital platforms are indeed valuable from the communication perspective to be proactive in the event of a similar situation. Moreover, significant themes, including social media adaptivity, absence of knowledge-providing mechanism and perception of safety measures of the vaccine, are the critical parameters leading to an amplified effect on vaccine hesitancy.

Practical implications

The COVID-19 Vaccine Hesitancy Amplification Themes (CVHAT) equips stakeholders and government strategists with a preconfigured paradigm to tackle dedicated communication campaigns and assess digital community behavior during health emergencies COVID-19.

Social implications

The increased acceptance of vaccines and the following of CAB decrease the advocacy of mutation of the virus and promote the healthy being of the people. As CAB has been mentioned as a preventive strategy against the COVID-19 pandemic, the research preposition promotes communication intervention which helps to mitigate future such pandemics. As developing, economies require effective communication strategies for vaccine acceptance and CAB, this study contributes to filling the gap using a digital environment.

Originality/value

Chan et al. (2020) recommended using social media platforms for public knowledge dissemination. The study observed that the value of a communication strategy is increased when communication happens using highly trusted and accessible channels such as Twitter and Facebook. With the preceding context, the present study is a novel approach to contribute toward digital communication strategies related to vaccination and CAB.

Citation

Yadav, H. and Sagar, M. (2023), "Exploring COVID-19 vaccine hesitancy and behavioral themes using social media big-data: a text mining approach", Kybernetes, Vol. 52 No. 7, pp. 2616-2648. https://doi.org/10.1108/K-06-2022-0810