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Public sentiment on Covid-19 vaccination rollout through Twitter content analysis

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  • Guilbert Nicanor Abiera Atillo

    (Negros Oriental State University, Dumaguete City)

Abstract

This study looks at what people are saying about Covid-19 vaccines on Twitter. Text mining techniques and sentiment analysis were used to analyze the tweets and see what patterns and trends emerged. The study found that most tweets were positive, showing hope and confidence in vaccines. People believe vaccines can help reduce deaths, severe illness, and the spread of the virus. However, the result also noticed that people express different emotions like sadness, fear, joy, and surprise in their tweets. These emotions can change based on how people feel and what’s happening around them. Understanding how people think about Covid-19 vaccines can help policymakers, doctors, and community leaders. It can guide them in addressing concerns, sharing accurate information, and building vaccine trust. This can ultimately help in the fight against the pandemic.

Suggested Citation

  • Guilbert Nicanor Abiera Atillo, 2025. "Public sentiment on Covid-19 vaccination rollout through Twitter content analysis," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - SOCIAL SCIENCES, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 15(5), pages 73-85.
    • Handle: RePEc:bjw:socien:v:15:y:2025:i:5:p:73-85
    DOI: 10.46223/HCMCOUJS.soci.en.15.3.3334.2025
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    References listed on IDEAS

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    2. Yanliang Qi, 2013. "Text Mining in Bioinformatics: Research and Application," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 3(2), pages 30-39, April.
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