Assessing RTS, S malaria vaccine rollout perception in Cameroon: Sentiment analysis from X and facebook using hugging face

<b>Background:</b> The introduction of the RTS, S (Mosquirix®) malaria vaccine in Cameroon represents a significant public health milestone. This study analyzed social media sentiment surrounding the vaccine rollout using natural language processing and machine learning. <b>Methods:</b> Data from Twitter (X) and Facebook (Meta) regarding the RTS, S vaccine in Cameroon was analyzed using the Hugging Face Transformer library for sentiment evaluation. The data was pre-processed, cleaned, and visualized with Matplotlib. <b>Results:</b> The sentiment analysis revealed that 42.0% of reactions were negative, 40.0% were positive, and 18.0% were neutral, indicating a nearly even split between skeptical and supportive viewpoints among Cameroonian users regarding the vaccine rollout. <b>Conclusion:</b> The research highlights the necessity for targeted communication strategies to address public concerns and foster vaccine confidence. Sentiment analysis can act as a real-time tool, offering policymakers valuable insights into public reactions and attitudes toward immunization and other health initiatives. These findings reveal significant public skepticism that must be addressed through evidence-based communication strategies focused on vaccine safety, efficacy data from pilot programs, and engagement with community leaders to counter misinformation.

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Publication Details

Journal
Health Informatics Journal
Published
2026-01-01
DOI
https://doi.org/10.1177/14604582261416864
Primary Topic
Vaccine Coverage and Hesitancy
Type
article
Field-Weighted Citation Impact
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article

Assessing RTS, S malaria vaccine rollout perception in Cameroon: Sentiment analysis from X and facebook using hugging face

Njinju Zilefac Fogap, Melvin Njuaka, Nana Koomson, Adanze Nge Cynthia
Health Informatics Journal
Vaccine Coverage and Hesitancy
article

Assessing RTS, S malaria vaccine rollout perception in Cameroon: Sentiment analysis from X and facebook using hugging face

Njinju Zilefac Fogap, Melvin Njuaka, Nana Koomson, Adanze Nge Cynthia
article en

Abstract

<b>Background:</b> The introduction of the RTS, S (Mosquirix®) malaria vaccine in Cameroon represents a significant public health milestone. This study analyzed social media sentiment surrounding the vaccine rollout using natural language processing and machine learning. <b>Methods:</b> Data from Twitter (X) and Facebook (Meta) regarding the RTS, S vaccine in Cameroon was analyzed using the Hugging Face Transformer library for sentiment evaluation. The data was pre-processed, cleaned, and visualized with Matplotlib. <b>Results:</b> The sentiment analysis revealed that 42.0% of reactions were negative, 40.0% were positive, and 18.0% were neutral, indicating a nearly even split between skeptical and supportive viewpoints among Cameroonian users regarding the vaccine rollout. <b>Conclusion:</b> The research highlights the necessity for targeted communication strategies to address public concerns and foster vaccine confidence. Sentiment analysis can act as a real-time tool, offering policymakers valuable insights into public reactions and attitudes toward immunization and other health initiatives. These findings reveal significant public skepticism that must be addressed through evidence-based communication strategies focused on vaccine safety, efficacy data from pilot programs, and engagement with community leaders to counter misinformation.

Health Informatics JournalVol. 32(1)
Sanko University (TR), Afya na Haki Institute (UG)
Good health and well-being
Openalex Percentile: Top 95%
Vaccine Coverage and Hesitancy
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Assessing RTS, S malaria vaccine rollout perception in Cameroon: Sentiment analysis from X and facebook using hugging face — Njinju Zilefac Fogap, Melvin Njuaka, et al. · Health Informatics Journal (2026) | TGRS Research Map | TGRS