{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T22:51:34Z","timestamp":1768690294910,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684567","type":"print"},{"value":"9781643684574","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T00:00:00Z","timestamp":1706140800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,25]]},"abstract":"<jats:p>Vaccine hesitancy represents a barrier to public health efforts aiming to mitigate the pandemic by performing global interventions. One of the reasons behind vaccine hesitancy is mistrust towards the health system that partially originated due to the misinformation shared over the internet. This study examined the association between the credibility of the sources regarding the COVID-19 vaccine posted on social media and the vaccination rate at the state level in the United States. Study findings suggest that sharing more Facebook posts with links to low-credibility sources about vaccination is associated with a lower number of new vaccinations at the state level in the US. This indicates an urgent need for social media-leveraged interventions through which public health officials can share reliable information to educate populations about vaccine benefits and reduce vaccine hesitancy.<\/jats:p>","DOI":"10.3233\/shti231111","type":"book-chapter","created":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:26:12Z","timestamp":1706178372000},"source":"Crossref","is-referenced-by-count":2,"title":["Facebook Post Credibility as a Predictor of Vaccine Hesitancy in the US"],"prefix":"10.3233","author":[{"given":"Ana","family":"Aleksandric","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, The University of Texas at Arlington, United States"},{"name":"Multi-Interprofessional Center for Health Informatics, The University of Texas at Arlington, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anisha","family":"Dangal","sequence":"additional","affiliation":[{"name":"Multi-Interprofessional Center for Health Informatics, The University of Texas at Arlington, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shirin","family":"Nilizadeh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, The University of Texas at Arlington, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3090-9242","authenticated-orcid":false,"given":"Gabriela","family":"Mustata Wilson","sequence":"additional","affiliation":[{"name":"Multi-Interprofessional Center for Health Informatics, The University of Texas at Arlington, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2023 \u2014 The Future Is Accessible"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI231111","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,25]],"date-time":"2024-01-25T10:26:13Z","timestamp":1706178373000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI231111"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,25]]},"ISBN":["9781643684567","9781643684574"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti231111","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,25]]}}}