Malaysian views on COVID-19 vaccination program: a sentiment analysis study using Twitter

Mohamed Imran Mohamed Ariff, Nurul Erina Shuhada Zubir, Azilawati Azizan, Samsiah Ahmad, Noreen Izza Arshad

Abstract


This study aimed to analyze the opinions and emotions of Malaysians towards the COVID-19 vaccination program, as expressed on Twitter. By collecting data from the Twitter network and utilizing the machine learning life cycle technique. The results show that Malaysians have a mostly neutral viewpoint of the COVID-19 vaccination, with an accuracy score of 93%, an F1-score of 94%, a recall measurement of 94%, and a precision measure of 93%. These findings emphasize the significance of understanding public sentiment and perception towards crucial issues such as the COVID-19 vaccine and can be utilized to support healthcare professionals, policymakers, and the public in making informed decisions regarding the COVID-19 vaccination program.

Keywords


COVID-19; Data mining; Opinion mining; Sentiment analysis; Twitter

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DOI: https://doi.org/10.11591/eei.v13i1.6097

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Bulletin of EEI Stats

Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191, e-ISSN: 2302-9285
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