{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T17:57:47Z","timestamp":1793383067270,"version":"4.5.0"},"reference-count":62,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:p>\n                    <jats:bold>Background:<\/jats:bold>\n                    The introduction of the RTS, S (Mosquirix\u00ae) 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.\n                    <jats:bold>Methods:<\/jats:bold>\n                    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.\n                    <jats:bold>Results:<\/jats:bold>\n                    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.\n                    <jats:bold>Conclusion:<\/jats:bold>\n                    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.\n                  <\/jats:p>","DOI":"10.1177\/14604582261416864","type":"journal-article","created":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:12:16Z","timestamp":1767917536000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Assessing RTS, S malaria vaccine rollout perception in Cameroon: Sentiment analysis from X and facebook using hugging face"],"prefix":"10.1177","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3802-9653","authenticated-orcid":false,"given":"Adanze Nge","family":"Cynthia","sequence":"first","affiliation":[{"name":"Sankofa Research and Mentorship Hub"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melvin","family":"Njuaka","sequence":"additional","affiliation":[{"name":"Sankofa Research and Mentorship Hub"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nana","family":"Koomson","sequence":"additional","affiliation":[{"name":"Afya na Haki"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Njinju Zilefac","family":"Fogap","sequence":"additional","affiliation":[{"name":"Sankofa Research and Mentorship Hub"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"e_1_3_6_2_2","volume-title":"WHO. 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