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Can Post-vaccination Sentiment Affect the Acceptance of Booster Jab?

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Intelligent Systems Design and Applications (ISDA 2022)

Abstract

In this paper, Twitter posts discussing the COVID-19 vaccine booster shot from nine African countries were classified according to sentiments to understand the effect of citizens’ sentiments towards accepting the booster shot. The number of booster shot-related tweets significantly positively correlated with the increase in booster shots across different countries (Corr = 0.410, P = 0.028). Similarly, the increase in the number of positive tweets discussing booster shots significantly positively correlated with the increase in positive tweet intensities (Corr = 0.992, P\(\,<\,\)0.001). The increase in intensities of positive tweets also positively correlated with an increase in likes and re-tweets (Corr = 0.560, P\(\,<\,\)0.001). Topics were identified from the tweets using the LDA model, including – booster safety, booster efficacy, booster type, booster uptake, and vaccine uptake. The 77% of tweets discussing these topics are mostly from South Africa, Nigeria (19%), and Namibia (3%). Our result showed that there is an average 45.5% chance of tweets discussing these topics carrying positive sentiments. The outcome suggests that users’ expressions on social media regarding booster shots could likely affect the acceptance of booster shots either positively or negatively. This research should be relevant to health policy-makers in gathering insight from social media data for the management and planning of vaccination programs during a disease outbreak.

This research is funded by Canada’s International Development Research Centre (IDRC) and the Swedish International Development Cooperation Agency (SIDA) (Grant No. 109559-001). JDK acknowledges support from IDRC (Grant No. 109981), New Frontier in Research Fund- Exploratory (Grant No. NFRFE-2021-00879) and NSERC Discovery Grant (Grant No. RGPIN-2022-04559). B.O. and JDK acknowledges support from the Dahdaleh Institute for Global Health Research. The authors wish to acknowledge the Africa-Canada AI & Data Innovation Consortium (ACADIC) team at York University, Toronto, Canada and University of the Witwatersrand Johannesburg, South Africa.

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References

  1. Africa centre for disease control and prevention, April 2022. available Online. Accessed 10 June 2022

    Google Scholar 

  2. Al-Zaman, M.: Covid-19-related social media fake news in India. J. Media 2(5), 100–114 (2021)

    Google Scholar 

  3. Aljedaani, W., et al.: Sentiment analysis on twitter data integrating textBlob and deep learning models: the case of us airline industry. Knowl.-Based Syst. 255, 109780 (2022)

    Article  Google Scholar 

  4. Angyal, A., et al.: T-cell and antibody responses to first bnt162b2 vaccine dose in previously infected and SARS-COV-2-Naive UK health-care workers: a multicentre prospective cohort study. Lancet Microbe 3(1), e21–e31 (2022)

    Article  Google Scholar 

  5. Ganguly, S., Morapakula, S.N., Coronado, L.M.P.: Quantum natural language processing based sentiment analysis using lambeq toolkit. In: 2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T), pp. 1–6 (2022)

    Google Scholar 

  6. Ghai, S., Magis-Weinberg, L., Stoilova, M., Livingstone, S., Orben, A.: Social media and adolescent well-being in the global south. Curr. Opin. Psychol. 46, 101318 (2022)

    Article  Google Scholar 

  7. Hogan, M.J., Pardi, N.: mRNA vaccines in the Covid-19 pandemic and beyond. Annu. Rev. Med. 73, 17–39 (2022)

    Google Scholar 

  8. Honnibal, M.: spacy 2: Natural language understanding with bloom embeddings, convolutional neural networks and incremental parsing. Sentometrics Res. 1(1), 2586–2593 (2017)

    Google Scholar 

  9. Hussain, A., et al.: MRNA vaccines for Covid-19 and diverse diseases. J. Control. Release 345, 314–333 (2022)

    Article  Google Scholar 

  10. Jang, H., Rempel, E., Roe, I., Adu, P., Carenini, G., Janjua, N.Z.: Tracking public attitudes toward Covid-19 vaccination on tweets in Canada: using aspect-based sentiment analysis. J. Med. Internet Res. 24(3), e35016 (2022)

    Article  Google Scholar 

  11. Kesselheim, A.S., et al.: An overview of vaccine development, approval, and regulation, with implications for COVID-19. Health Aff. 40(1) (2020)

    Google Scholar 

  12. Lavelle, E., Ward, R.: Mucosal vaccines - fortifying the frontiers. Nat. Rev. Immunol. 22, 236–250 (2022)

    Google Scholar 

  13. Lawal, L., et al.: Low coverage of Covid-19 vaccines in Africa: current evidence and the way forward. Hum. Vaccines Immunotherapeutics 18(1), 2034457 (2022)

    Article  Google Scholar 

  14. Li, F., et al.: What’s new in pandas 1.2.4. Available online. Accessed 01 June 2022

    Google Scholar 

  15. Marcec, R., Likic, R.: Using Twitter for sentiment analysis towards Astrazeneca/Oxford, Pfizer/Biontech and Moderna Covid-19 vaccines. Postgrad. Med. J. 10(5), 1–7 (2021)

    Google Scholar 

  16. Medeiros, K.S., Costa, A.P.F., Sarmento, A.C.A., Freitas, C.L., Gonçalves, A.K.: Side effects of Covid-19 vaccines: a systematic review and meta-analysis protocol of randomised trials. BMJ Open 12(2) (2022)

    Google Scholar 

  17. Morens, D.M., Taubenberger, J.K., Fauci, A.S.: Universal coronavirus vaccines - an urgent need. N. Engl. J. Med. 386(4), 297–299 (2022). pMID: 34910863

    Google Scholar 

  18. Obaido, G., et al.: An interpretable machine learning approach for hepatitis b diagnosis. Appl. Sci. 12(21) (2022)

    Google Scholar 

  19. Ogbuokiri, B., et al.: Public sentiments toward Covid-19 vaccines in South African cities: an analysis of twitter posts. Front. Publ. Health 10, 987376 (2022)

    Article  Google Scholar 

  20. Ogbuokiri, B., et al.: Vaccine hesitancy hotspots in Africa: an insight from geotagged Twitter posts. TechRxiv, Preprint (2022)

    Google Scholar 

  21. Ogbuokiri, B., et al.: Determining the impact of omicron variant in vaccine uptake in South Africa using Twitter data. Submitted to Nat. Lang. Process. J. (2022)

    Google Scholar 

  22. Ritskes-Hoiting, M., Barell, Y., Kleinhout-Vliek, T.: The promises of speeding up: changes in requirements for animal studies and alternatives during Covid-19 vaccine approval-a case study. Animals 12(13), 1735 (2022)

    Article  Google Scholar 

  23. Tasnim, S., Hossain, M., Mazumder, H.: Impact of rumors and misinformation on Covid-19 in social media. J. Prev. Med. Publ. Health 202(53), 171–174 (2021)

    Google Scholar 

  24. van Gils, M.J., et al.: A single MRNA vaccine dose in Covid-19 patients boosts neutralizing antibodies against SARS-COV-2 and variants of concern. Cell Rep. Med. 3(1), 100486 (2022)

    Article  Google Scholar 

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Correspondence to Blessing Ogbuokiri or Jude Kong .

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Ogbuokiri, B. et al. (2023). Can Post-vaccination Sentiment Affect the Acceptance of Booster Jab?. In: Abraham, A., Pllana, S., Casalino, G., Ma, K., Bajaj, A. (eds) Intelligent Systems Design and Applications. ISDA 2022. Lecture Notes in Networks and Systems, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-031-35501-1_20

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