Public Sentiment Analysis in Social Media on the SARS-CoV-2 Vaccination Using VADER Lexicon Polarity

Author:

Algaraady Dr. Jeehaan,Mahyoob Dr. Mohammad

Abstract

    Recently Natural Language Processing (NLP) constituted an important area of computational linguistics and artificial intelligence, where the virtual and digital world has become an essential aspect of our daily lives. Sentiment analysis and data mining are sub-fields of NLP, which draw the attention of researchers to search and mine various issues on social media. This study explores the public's sentiments and opinions towards the SARS-CoV-2 vaccination doses in Saudi Arabia. It tries to provide insights on the motivations and barriers in taking the first and second vaccine doses and how the public's awareness and attitudes differ in the two doses. The research objects are 6.232 public tweets and comments that have been harvested from official social media platforms (Twitter and YouTube) between December 19, 2020, and December 10, 2021. The sentiment analysis measured polarity using the NLTK VADER analyzer, and the opinions were identified and classified based on the multidimensional scaling method. The results show that in the case of the first vaccine dose of the 2989 opinions enrolled, 61.5% of the public were willing to take the COVID-19 vaccination—the majority trust the vaccine safety and the Ministry of Health measures and decisions. While 21.1% show negative attitudes towards the vaccination, most of them untrust the vaccine and are worried about its syndromes. In the case of the second vaccine dose of the 3,243 opinions enrolled, 63.2% also show positive attitudes towards taking the vaccine. Trusting the vaccine safety and not being prevented from work, travel, and other activities are the primary motivations to receive the vaccine in this phase. While negative sentiments scored 30.3%, the most frequent determinant is the suspicion of the vaccine safety, symptoms, and decision discrepancies. Identifying public sentiments and attitudes toward COVID-19 vaccination would provide a better understanding of the reasons behind vaccine rejection or acceptance would help the health policymakers better develop and implement vaccine awareness strategies and appropriate communication to enhance vaccine taking.

Publisher

Taiz University

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Challenges and Sustainability of E-Learning Adoption Among EFL Teachers in the Post-COVID-19 Era;Advances in Educational Technologies and Instructional Design;2024-06-30

2. A Deterministic Finite-State Morphological Analyzer for Urdu Nominal System;Engineering, Technology & Applied Science Research;2023-06-02

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