Extracting factors associated with vaccination from Twitter data and mapping to behavioral models

ABSTRACT

Social media platform, particularly Twitter, is a rich data source that allows monitoring of public opinions and attitudes toward vaccines.Established behavioral models like the 5C psychological antecedents model and the Health Belief Model (HBM) provide a well-structured framework for analyzing shifts in vaccine-related behavior. This study examines if the extracted data from Twitter contains valuable insights regarding public attitudes toward vaccines and can be mapped to two behavioral models. This study focuses on the Arab population, and a search was carried out on Twitter using: ’ تلقيحي OR تطعيم OR تطعيمات OR لقاح OR لقاحات’ for two years from January 2020 to January 2022. Then, BERTopicmodeling was applied, and several topics were extracted. Finally, the topics were manually mapped to the factors of the 5C model and HBM. 1,068,466 unique users posted 3,368,258 vaccine-related tweets in Arabic. Topic modeling generated 25 topics, which were mapped to the 15 factors of the 5C model and HBM. Among the users, 32.87%were male, and 18.06% were female. A significant 55.77% of the users were from the MENA (Middle East and North Africa) region. Twitter users were more inclined to accept vaccines when they trusted vaccine safety and effectiveness, but vaccine hesitancy increased due to conspiracy theories and misinformation. The association of topics with these theoretical frameworks reveals the availability and diversity of Twitter data that can predict behavioral change toward vaccines. It allows the preparation of timely and effective interventions for vaccination programs compared to traditional methods.

KEYWORDS:

• COVID-19
• vaccination
• behavior
• attitudes
• 5C model
• health belief model

Acknowledgments

Open Access funding provided by Qatar National Library.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

Conceptualization: Z.S. Research and Writing: M.R.B. and Z.S. Analyses and Figures: M.R.B. Topic modeling and labeling: M.R.B. Twitter Data Acquisition: M.R.B. Discussion: M.R.B. and Z.S. Manuscript review: M.R.B. and Z.S.

Data availability statement

Vaccine-related Twitter data is available on request for research purposes only and can be requested by emailing author M.R.B. [email protected]

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/21645515.2023.2281729.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.