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For: Tomeny TS, Vargo CJ, El-Toukhy S. Geographic and demographic correlates of autism-related anti-vaccine beliefs on Twitter, 2009-15. Soc Sci Med 2017;191:168-75. [PMID: 28926775 DOI: 10.1016/j.socscimed.2017.08.041] [Cited by in Crossref: 58] [Cited by in F6Publishing: 35] [Article Influence: 14.5] [Reference Citation Analysis]
Number Citing Articles
1 Gabutti G, Carioli U, Gamberoni D, Masetti G, Matteo G, Perrone P, Cappadona R, Greco P, Siliquini R, Stefanati A. Use of Information Sources on Vaccine-Preventable Diseases in Pregnant Women: An Experience in Ferrara, Italy. Int J Environ Res Public Health 2019;17:E233. [PMID: 31905635 DOI: 10.3390/ijerph17010233] [Reference Citation Analysis]
2 [DOI: 10.2196/preprints.17149] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
3 On J, Park HA, Song TM. Sentiment Analysis of Social Media on Childhood Vaccination: Development of an Ontology. J Med Internet Res 2019;21:e13456. [PMID: 31199290 DOI: 10.2196/13456] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
4 Amith M, Cohen T, Cunningham R, Savas LS, Smith N, Cuccaro P, Gabay E, Boom J, Schvaneveldt R, Tao C. Mining HPV Vaccine Knowledge Structures of Young Adults From Reddit Using Distributional Semantics and Pathfinder Networks. Cancer Control 2020;27:1073274819891442. [PMID: 31912742 DOI: 10.1177/1073274819891442] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
5 Skafle I, Gabarron E, Dechsling A, Nordahl-Hansen A. Online Attitudes and Information-Seeking Behavior on Autism, Asperger Syndrome, and Greta Thunberg. Int J Environ Res Public Health 2021;18:4981. [PMID: 34067114 DOI: 10.3390/ijerph18094981] [Reference Citation Analysis]
6 Bonnevie E, Goldbarg J, Gallegos-Jeffry AK, Rosenberg SD, Wartella E, Smyser J. [Content Themes and Influential Voices Within Vaccine Opposition on Twitter, 2019]. Rev Panam Salud Publica 2021;45:e54. [PMID: 33995521 DOI: 10.26633/RPSP.2021.54] [Reference Citation Analysis]
7 Bonnevie E, Goldbarg J, Gallegos-Jeffrey AK, Rosenberg SD, Wartella E, Smyser J. Content Themes and Influential Voices Within Vaccine Opposition on Twitter, 2019. Am J Public Health 2020;110:S326-30. [PMID: 33001733 DOI: 10.2105/AJPH.2020.305901] [Cited by in Crossref: 10] [Cited by in F6Publishing: 3] [Article Influence: 10.0] [Reference Citation Analysis]
8 Pullan S, Dey M. Vaccine hesitancy and anti-vaccination in the time of COVID-19: A Google Trends analysis. Vaccine 2021;39:1877-81. [PMID: 33715904 DOI: 10.1016/j.vaccine.2021.03.019] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 11.0] [Reference Citation Analysis]
9 Tulloch JSP, Vivancos R, Christley RM, Radford AD, Warner JC. Mapping tweets to a known disease epidemiology; a case study of Lyme disease in the United Kingdom and Republic of Ireland. J Biomed Inform 2019;100S:100060. [PMID: 34384577 DOI: 10.1016/j.yjbinx.2019.100060] [Cited by in Crossref: 5] [Article Influence: 2.5] [Reference Citation Analysis]
10 Pivetti M, Melotti G, Mancini C. Vaccines and autism: a preliminary qualitative study on the beliefs of concerned mothers in Italy. Int J Qual Stud Health Well-being 2020;15:1754086. [PMID: 32298221 DOI: 10.1080/17482631.2020.1754086] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
11 Jamison A, Broniatowski DA, Smith MC, Parikh KS, Malik A, Dredze M, Quinn SC. Adapting and Extending a Typology to Identify Vaccine Misinformation on Twitter. Am J Public Health 2020;110:S331-9. [PMID: 33001737 DOI: 10.2105/AJPH.2020.305940] [Cited by in Crossref: 11] [Cited by in F6Publishing: 5] [Article Influence: 11.0] [Reference Citation Analysis]
12 Argyris YA, Monu K, Tan PN, Aarts C, Jiang F, Wiseley KA. Using Machine Learning to Compare Provaccine and Antivaccine Discourse Among the Public on Social Media: Algorithm Development Study. JMIR Public Health Surveill 2021;7:e23105. [PMID: 34185004 DOI: 10.2196/23105] [Reference Citation Analysis]
13 Cai M, Shah N, Li J, Chen WH, Cuomo RE, Obradovich N, Mackey TK. Identification and characterization of tweets related to the 2015 Indiana HIV outbreak: A retrospective infoveillance study. PLoS One 2020;15:e0235150. [PMID: 32845882 DOI: 10.1371/journal.pone.0235150] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
14 Tomaszewski T, Morales A, Lourentzou I, Caskey R, Liu B, Schwartz A, Chin J. Identifying False Human Papillomavirus (HPV) Vaccine Information and Corresponding Risk Perceptions From Twitter: Advanced Predictive Models. J Med Internet Res 2021;23:e30451. [PMID: 34499043 DOI: 10.2196/30451] [Reference Citation Analysis]
15 Bonnevie E, Gallegos-jeffrey A, Goldbarg J, Byrd B, Smyser J. Quantifying the rise of vaccine opposition on Twitter during the COVID-19 pandemic. Journal of Communication in Healthcare 2021;14:12-9. [DOI: 10.1080/17538068.2020.1858222] [Cited by in Crossref: 23] [Cited by in F6Publishing: 1] [Article Influence: 23.0] [Reference Citation Analysis]
16 Miller M, Romine W, Oroszi T. Public Discussion of Anthrax on Twitter: Using Machine Learning to Identify Relevant Topics and Events. JMIR Public Health Surveill 2021;7:e27976. [PMID: 34142975 DOI: 10.2196/27976] [Reference Citation Analysis]
17 Luyten J, Kessels R, Atkins KE, Jit M, van Hoek AJ. Quantifying the public's view on social value judgments in vaccine decision-making: A discrete choice experiment. Soc Sci Med 2019;228:181-93. [PMID: 30925392 DOI: 10.1016/j.socscimed.2019.03.025] [Cited by in Crossref: 11] [Cited by in F6Publishing: 9] [Article Influence: 5.5] [Reference Citation Analysis]
18 Meah VL, Kimber ML, Simpson J, Davenport MH. Knowledge translation and social media: Twitter data analysis of the 2019 Canadian Guideline for Physical Activity throughout Pregnancy. Can J Public Health 2020;111:1049-56. [PMID: 32902831 DOI: 10.17269/s41997-020-00393-4] [Reference Citation Analysis]
19 Piedrahita-Valdés H, Piedrahita-Castillo D, Bermejo-Higuera J, Guillem-Saiz P, Bermejo-Higuera JR, Guillem-Saiz J, Sicilia-Montalvo JA, Machío-Regidor F. Vaccine Hesitancy on Social Media: Sentiment Analysis from June 2011 to April 2019. Vaccines (Basel) 2021;9:28. [PMID: 33430428 DOI: 10.3390/vaccines9010028] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 12.0] [Reference Citation Analysis]
20 Tang L, Fujimoto K, Amith MT, Cunningham R, Costantini RA, York F, Xiong G, Boom JA, Tao C. "Down the Rabbit Hole" of Vaccine Misinformation on YouTube: Network Exposure Study. J Med Internet Res 2021;23:e23262. [PMID: 33399543 DOI: 10.2196/23262] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
21 Frew PM, Paine MB, Rouphael N, Schamel J, Chung Y, Mulligan MJ, Prausnitz MR. Acceptability of an inactivated influenza vaccine delivered by microneedle patch: Results from a phase I clinical trial of safety, reactogenicity, and immunogenicity. Vaccine 2020;38:7175-81. [PMID: 32792250 DOI: 10.1016/j.vaccine.2020.07.064] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
22 Arendt F, Scherr S. Investigating an Issue-Attention-Action Cycle: A Case Study on the Chronology of Media Attention, Public Attention, and Actual Vaccination Behavior during the 2019 Measles Outbreak in Austria. J Health Commun 2019;24:654-62. [PMID: 31423919 DOI: 10.1080/10810730.2019.1652709] [Cited by in Crossref: 8] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
23 Haynes E, Garside R, Green J, Kelly MP, Thomas J, Guell C. Semiautomated text analytics for qualitative data synthesis. Res Synth Methods 2019;10:452-64. [PMID: 31125493 DOI: 10.1002/jrsm.1361] [Cited by in Crossref: 13] [Cited by in F6Publishing: 3] [Article Influence: 6.5] [Reference Citation Analysis]
24 Jiménez ÁV, Stubbersfield JM, Tehrani JJ. An experimental investigation into the transmission of antivax attitudes using a fictional health controversy. Social Science & Medicine 2018;215:23-7. [DOI: 10.1016/j.socscimed.2018.08.032] [Cited by in Crossref: 12] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
25 Barry A, Bottasso OA, Vicco MH. The importance of being scientifically cautious when criticizing the administration of vaccines: ‘retracted’ post truth. Immunotherapy 2019;11:7-9. [DOI: 10.2217/imt-2018-0062] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
26 Rubenstein E, Furnier S. #Bias: The Opportunities and Challenges of Surveys That Recruit and Collect Data of Autistic Adults Online. Autism Adulthood 2021;3:120-8. [PMID: 34169230 DOI: 10.1089/aut.2020.0031] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
27 Karafillakis E, Martin S, Simas C, Olsson K, Takacs J, Dada S, Larson HJ. Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review. JMIR Public Health Surveill 2021;7:e17149. [PMID: 33555267 DOI: 10.2196/17149] [Cited by in Crossref: 9] [Cited by in F6Publishing: 4] [Article Influence: 9.0] [Reference Citation Analysis]
28 Yalçin SS, Bakacak AG, Topaç O. Unvaccinated children as community parasites in National Qualitative Study from Turkey. BMC Public Health 2020;20:1087. [PMID: 32652961 DOI: 10.1186/s12889-020-09184-5] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
29 Broniatowski DA, Jamison AM, Qi S, AlKulaib L, Chen T, Benton A, Quinn SC, Dredze M. Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate. Am J Public Health 2018;108:1378-84. [PMID: 30138075 DOI: 10.2105/AJPH.2018.304567] [Cited by in Crossref: 339] [Cited by in F6Publishing: 100] [Article Influence: 113.0] [Reference Citation Analysis]
30 Muric G, Wu Y, Ferrara E. COVID-19 Vaccine Hesitancy on Social Media: Building a Public Twitter Data Set of Antivaccine Content, Vaccine Misinformation, and Conspiracies. JMIR Public Health Surveill 2021;7:e30642. [PMID: 34653016 DOI: 10.2196/30642] [Reference Citation Analysis]
31 Abila DB, Dei-Tumi SD, Humura F, Aja GN. We need to start thinking about promoting the demand, uptake, and equitable distribution of COVID-19 vaccines NOW! Public Health Pract (Oxf) 2020;1:100063. [PMID: 34173585 DOI: 10.1016/j.puhip.2020.100063] [Cited by in Crossref: 6] [Article Influence: 6.0] [Reference Citation Analysis]
32 Shah Z, Surian D, Dyda A, Coiera E, Mandl KD, Dunn AG. Automatically Appraising the Credibility of Vaccine-Related Web Pages Shared on Social Media: A Twitter Surveillance Study. J Med Internet Res 2019;21:e14007. [PMID: 31682571 DOI: 10.2196/14007] [Cited by in Crossref: 15] [Cited by in F6Publishing: 8] [Article Influence: 7.5] [Reference Citation Analysis]
33 Dixon G. Undermining Credibility: The Limited Influence of Online Comments to Vaccine-related News Stories. J Health Commun 2020;25:943-50. [PMID: 33404379 DOI: 10.1080/10810730.2020.1865485] [Reference Citation Analysis]
34 To QG, To KG, Huynh VN, Nguyen NTQ, Ngo DTN, Alley SJ, Tran ANQ, Tran ANP, Pham NTT, Bui TX, Vandelanotte C. Applying Machine Learning to Identify Anti-Vaccination Tweets during the COVID-19 Pandemic. Int J Environ Res Public Health 2021;18:4069. [PMID: 33921539 DOI: 10.3390/ijerph18084069] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
35 Sonawane K, Lin YY, Damgacioglu H, Zhu Y, Fernandez ME, Montealegre JR, Cazaban CG, Li R, Lairson DR, Lin Y, Giuliano AR, Deshmukh AA. Trends in Human Papillomavirus Vaccine Safety Concerns and Adverse Event Reporting in the United States. JAMA Netw Open 2021;4:e2124502. [PMID: 34533574 DOI: 10.1001/jamanetworkopen.2021.24502] [Reference Citation Analysis]