IDEAS home Printed from https://ideas.repec.org/a/bjw/socien/v15y2025i5p73-85.html

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journalofscience.ou.edu.vn/index.php/soci-en/article/view/3334/2207
    Download Restriction: no
    File URL: https://libkey.io/10.46223/HCMCOUJS.soci.en.15.3.3334.2025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Aaryan Gupta & Vinya Dengre & Hamza Abubakar Kheruwala & Manan Shah, 2020. "Comprehensive review of text-mining applications in finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.
    2. Yanliang Qi, 2013. "Text Mining in Bioinformatics: Research and Application," International Journal of Information Retrieval Research (IJIRR), IGI Global Scientific Publishing, vol. 3(2), pages 30-39, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenlu Zhao & Guanghu Jin & Chenyue Huang & Jinji Zhang, 2023. "Attention and Sentiment of the Chinese Public toward a 3D Greening System Based on Sina Weibo," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    2. Cotrina-Teatino, Marco A. & Marquina-Araujo, Jairo J. & Mamani-Quispe, Jose N. & Arango-Retamozo, Solio M. & Gonzalez-Vasquez, Joe A., 2025. "Bibliometric and systematic analysis of the literature on the Hartwick rule in non-renewable resources," Resources Policy, Elsevier, vol. 107(C).
    3. Christopher Gerling & Stefan Lessmann, 2023. "Multimodal Document Analytics for Banking Process Automation," Papers 2307.11845, arXiv.org, revised Nov 2023.
    4. Yali Li & Gaobin Du & Yilun Lu, 2025. "Management incentives, governance, and digital transformation: effects on financial disclosure integrity," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 49(4), pages 1115-1145, December.
    5. Kentaka Aruga & Md. Monirul Islam & Yoshihiro Zenno & Arifa Jannat, 2022. "Developing Novel Technique for Investigating Guidelines and Frameworks: A Text Mining Comparison between International and Japanese Green Bonds," JRFM, MDPI, vol. 15(9), pages 1-17, August.
    6. Yuanying Chi & Mingjian Yan & Yuexia Pang & Hongbo Lei, 2022. "Financial Risk Assessment of Photovoltaic Industry Listed Companies Based on Text Mining," Sustainability, MDPI, vol. 14(19), pages 1-17, September.
    7. Mazzotta, Stefano, 2022. "Immigration narrative sentiment from TV news and the stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    8. Kurowski, Łukasz & Smaga, Paweł, 2023. "Analysing financial stability reports as crisis predictors with the use of text-mining," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    9. Yang, Jie & Niu, Yanfang & Shi, Wenlei & Zhu, Kanghuan, 2025. "Predicting ESG disclosure quality through board secretaries' characteristics: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 76(C).
    10. Denisa Millo & Blerina Vika & Nevila Baci, 2024. "Integrating Natural Language Processing Techniques of Text Mining Into Financial System: Applications and Limitations," Papers 2412.20438, arXiv.org.
    11. Domenica Mino & Cillian Williamson, 2025. "Sentiment and Volatility in Financial Markets: A Review of BERT and GARCH Applications during Geopolitical Crises," Papers 2510.16503, arXiv.org.
    12. Mazzotta, Stefano, 2024. "Immigration Narrative and Home Prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 43(C).
    13. Poojan Thakkar & Manan Shah, 2021. "An Assessment of Football Through the Lens of Data Science," Annals of Data Science, Springer, vol. 8(4), pages 823-836, December.
    14. Sanaz Ghorbanloo & Sajjad Shokouhyar, 2023. "Consumers' attitude footprint on sustainable development in developed and developing countries: a case study in the electronic industry," Operations Management Research, Springer, vol. 16(3), pages 1444-1475, September.
    15. Li-Chen Cheng & Wei-Ting Lu & Benjamin Yeo, 2023. "Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    16. Xie, Haotian & Li, Yi & Pu, Yang & Zhang, Chen & Huang, Junlin, 2024. "Evaluating airline service quality through a comprehensive text-mining and multi-criteria decision-making analysis," Journal of Air Transport Management, Elsevier, vol. 120(C).
    17. Robert Kudelić & Tamara Šmaguc & Sherry Robinson, 2025. "Artificial intelligence in the service of entrepreneurial finance: knowledge structure and the foundational algorithmic paradigm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-43, December.
    18. Yinheng Li & Shaofei Wang & Han Ding & Hang Chen, 2023. "Large Language Models in Finance: A Survey," Papers 2311.10723, arXiv.org, revised Jul 2024.
    19. Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 61(C).
    20. Vyshnevskyi, Iegor & Jombo, Wytone & Sohn, Wook, 2024. "The clarity of monetary policy communication and financial market volatility in developing economies," Emerging Markets Review, Elsevier, vol. 59(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjw:socien:v:15:y:2025:i:5:p:73-85. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Vu Tuan Truong (email available below). General contact details of provider: https://journalofscience.ou.edu.vn/index.php/soci-en .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.