{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:07:16Z","timestamp":1782846436411,"version":"3.54.5"},"reference-count":38,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Infodemiology"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>As the prospect of an HIV vaccine nears reality, understanding public discourse around the vaccine is essential for informing communication strategies and addressing misinformation. Social media platforms are influential spaces where public narratives form, yet little research has examined discourse around an HIV vaccine, especially on TikTok.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to compare and characterize public discourse about a future HIV vaccine across Twitter (subsequently rebranded X) and TikTok, identifying prevailing themes, sentiments, and rhetorical strategies to inform public health communication.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>From over 400,000 tweets and 65,000 TikTok comments, we analyzed the 1000 most-liked posts on each platform using natural language processing and coded the top 500 most-liked posts for rhetorical strategies, sentiment, and themes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our findings reveal expressions of hope and trust in science on both platforms, as well as concerns about institutional corruption and conspiracy theories, such as the belief that the HIV vaccine responds to harm caused by the COVID-19 vaccine. Tweets tended to be more linguistically complex and yielded richer insights, while TikTok comments were shorter and more difficult to interpret without video context. Key rhetorical strategies included conspiracy theories, post hoc reasoning, and emotional appeals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study underscores the need for platform-specific communication strategies to address misinformation and build public trust. The findings offer timely insights into emerging HIV vaccine discourse and highlight actionable opportunities for public health stakeholders to build trust and combat misinformation in advance of the vaccine rollout.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/82917","type":"journal-article","created":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T19:45:09Z","timestamp":1770666309000},"page":"e82917-e82917","source":"Crossref","is-referenced-by-count":0,"title":["Social Media Perspectives on a Future HIV Vaccine: Mixed Methods Analysis"],"prefix":"10.2196","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0456-8588","authenticated-orcid":false,"given":"Megan A","family":"Rabin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7440-6085","authenticated-orcid":false,"given":"Sarah","family":"Penuela-Wermers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2532-8531","authenticated-orcid":false,"given":"Neil K R","family":"Sehgal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5492-0899","authenticated-orcid":false,"given":"Teniola I","family":"Egbe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5498-0209","authenticated-orcid":false,"given":"Criswell L M","family":"Lavery","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2929-0035","authenticated-orcid":false,"given":"Sharath Chandra","family":"Guntuku","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2432-1637","authenticated-orcid":false,"given":"Alison M","family":"Buttenheim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,3,19]]},"reference":[{"issue":"4","key":"R1","doi-asserted-by":"publisher","first-page":"1621","DOI":"10.4269\/ajtmh.20-0812","article-title":"COVID-19\u2013related infodemic and its impact on public health: a global social media analysis","volume":"103","author":"Islam","journal-title":"Am J Trop Med Hyg"},{"issue":"3","key":"R2","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1038\/s41562-021-01056-1","article-title":"Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA","volume":"5","author":"Loomba","journal-title":"Nat Hum Behav"},{"issue":"6","key":"R3","doi-asserted-by":"publisher","first-page":"e258","DOI":"10.1016\/S2589-7500(19)30136-0","article-title":"Vaccine misinformation and social media","volume":"1","author":"Burki","journal-title":"Lancet Digit Health"},{"issue":"10","key":"R4","doi-asserted-by":"publisher","DOI":"10.1098\/rsos.201199","article-title":"Susceptibility to misinformation about COVID-19 around the world","volume":"7","author":"Roozenbeek","journal-title":"R Soc Open Sci"},{"issue":"4","key":"R5","doi-asserted-by":"publisher","DOI":"10.2196\/26627","article-title":"Artificial intelligence-enabled analysis of public attitudes on Facebook and Twitter toward COVID-19 vaccines in the United Kingdom and the United States: observational study","volume":"23","author":"Hussain","journal-title":"J Med Internet Res"},{"issue":"6","key":"R6","doi-asserted-by":"publisher","DOI":"10.2196\/24564","article-title":"Characteristics of antivaccine messages on social media: systematic review","volume":"23","author":"Wawrzuta","journal-title":"J Med Internet Res"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.2196\/53375","article-title":"Public discourse, user reactions, and conspiracy theories on the X platform about HIV vaccines: data mining and content analysis","volume":"26","author":"Zhang","journal-title":"J Med Internet Res"},{"issue":"7-8","key":"R8","doi-asserted-by":"publisher","first-page":"1476","DOI":"10.1080\/21645515.2018.1560774","article-title":"A content analysis of HPV related posts on Instagram","volume":"15","author":"Basch","journal-title":"Hum Vaccin Immunother"},{"key":"R9","unstructured":"HIV vaccines. 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