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Analyzing society anti-vaccination attitudes towards COVID-19: combining latent dirichlet allocation and fuzzy association rule mining with a fuzzy cognitive map

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  • Nazmiye Eligüzel

    (Gaziantep Islam Science and Technology University)

Abstract

COVID-19 has been declared a pandemic and countries are tackling this disease either through preventative measures such as lockdown and sanitization or through curative ones such as medication, isolation, and so on. Some people believe that vaccination is the best way to prevent this disease, while others disagree. Society’s attitudes toward vaccination can be influenced by a variety of factors such as misunderstanding, ambiguity, lack of knowledge. The proposed study’s goal is to better understand people’s attitudes regarding vaccination by focusing on key topics related to COVID-19 anti-vaccine tweets. Tweets are obtained over a period based on the number of COVID-19 cases by utilizing the “anti-vaccine” keyword rather than the “vaccine” keyword. Furthermore, in addition to people perceptions and attitudes toward anti-vaccination, the causal relationship between each topic is investigated. As a result, latent dirichlet allocation (LDA), fuzzy association rule mining (FARM), fuzzy cognitive map (FCM), and fuzzy c-means are used to conduct a complete study. Topics are analyzed independently using clustering and scenario analysis. The findings demonstrate the most common topics in anti-vaccination tweets, as well as the influence of each topic on the others.

Suggested Citation

  • Nazmiye Eligüzel, 2023. "Analyzing society anti-vaccination attitudes towards COVID-19: combining latent dirichlet allocation and fuzzy association rule mining with a fuzzy cognitive map," Fuzzy Optimization and Decision Making, Springer, vol. 22(4), pages 669-696, December.
    • Handle: RePEc:spr:fuzodm:v:22:y:2023:i:4:d:10.1007_s10700-023-09407-5
    DOI: 10.1007/s10700-023-09407-5
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    References listed on IDEAS

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    1. Shianghau Wu, 2020. "A Fuzzy Association Rules Mining Analysis of the Influencing Factors on the Failure of oBike in Taiwan," Mathematics, MDPI, vol. 8(11), pages 1-18, October.
    2. Decui Liang & Zhuoyin Dai & Mingwei Wang & Jinjun Li, 2020. "Web celebrity shop assessment and improvement based on online review with probabilistic linguistic term sets by using sentiment analysis and fuzzy cognitive map," Fuzzy Optimization and Decision Making, Springer, vol. 19(4), pages 561-586, December.
    3. Charlotte Roe & Madison Lowe & Benjamin Williams & Clare Miller, 2021. "Public Perception of SARS-CoV-2 Vaccinations on Social Media: Questionnaire and Sentiment Analysis," IJERPH, MDPI, vol. 18(24), pages 1-21, December.
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