6.
Tavoschi L, Quattrone F, DAndrea E, Ducange P, Vabanesi M, Marcelloni F
. Twitter as a sentinel tool to monitor public opinion on vaccination: an opinion mining analysis from September 2016 to August 2017 in Italy. Hum Vaccin Immunother. 2020; 16(5):1062-1069.
PMC: 7227677.
DOI: 10.1080/21645515.2020.1714311.
View
7.
Hughes B, Miller-Idriss C, Piltch-Loeb R, Goldberg B, White K, Criezis M
. Development of a Codebook of Online Anti-Vaccination Rhetoric to Manage COVID-19 Vaccine Misinformation. Int J Environ Res Public Health. 2021; 18(14).
PMC: 8304769.
DOI: 10.3390/ijerph18147556.
View
8.
Smith T
. Vaccine Rejection and Hesitancy: A Review and Call to Action. Open Forum Infect Dis. 2017; 4(3):ofx146.
PMC: 5597904.
DOI: 10.1093/ofid/ofx146.
View
9.
Nadarevic L, Reber R, Helmecke A, Kose D
. Perceived truth of statements and simulated social media postings: an experimental investigation of source credibility, repeated exposure, and presentation format. Cogn Res Princ Implic. 2020; 5(1):56.
PMC: 7656226.
DOI: 10.1186/s41235-020-00251-4.
View
10.
Hagen L, Fox A, OLeary H, Dyson D, Walker K, Lengacher C
. The Role of Influential Actors in Fostering the Polarized COVID-19 Vaccine Discourse on Twitter: Mixed Methods of Machine Learning and Inductive Coding. JMIR Infodemiology. 2022; 2(1):e34231.
PMC: 9254747.
DOI: 10.2196/34231.
View
11.
Tangcharoensathien V, Calleja N, Nguyen T, Purnat T, DAgostino M, Garcia-Saiso S
. Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation. J Med Internet Res. 2020; 22(6):e19659.
PMC: 7332158.
DOI: 10.2196/19659.
View
12.
Berl R, Samarasinghe A, Roberts S, Jordan F, Gavin M
. Prestige and content biases together shape the cultural transmission of narratives. Evol Hum Sci. 2023; 3:e42.
PMC: 10427335.
DOI: 10.1017/ehs.2021.37.
View
13.
Jones A, Omer S, Bednarczyk R, Halsey N, Moulton L, Salmon D
. Parents' source of vaccine information and impact on vaccine attitudes, beliefs, and nonmedical exemptions. Adv Prev Med. 2012; 2012:932741.
PMC: 3469070.
DOI: 10.1155/2012/932741.
View
14.
Beers A, Schafer J, Kennedy I, Wack M, Spiro E, Starbird K
. Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election. Proc Int AAAI Conf Weblogs Soc Media. 2024; 17:59-71.
PMC: 11037522.
DOI: 10.1609/icwsm.v17i1.22126.
View
15.
Lucia V, Kelekar A, Afonso N
. COVID-19 vaccine hesitancy among medical students. J Public Health (Oxf). 2020; 43(3):445-449.
PMC: 7799040.
DOI: 10.1093/pubmed/fdaa230.
View
16.
Loomba S, de Figueiredo A, Piatek S, de Graaf K, Larson H
. Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA. Nat Hum Behav. 2021; 5(3):337-348.
DOI: 10.1038/s41562-021-01056-1.
View
17.
Gesser-Edelsburg A, Diamant A, Hijazi R, Mesch G
. Correcting misinformation by health organizations during measles outbreaks: A controlled experiment. PLoS One. 2018; 13(12):e0209505.
PMC: 6300261.
DOI: 10.1371/journal.pone.0209505.
View
18.
Wood M
. Propagating and Debunking Conspiracy Theories on Twitter During the 2015-2016 Zika Virus Outbreak. Cyberpsychol Behav Soc Netw. 2018; 21(8):485-490.
PMC: 6094351.
DOI: 10.1089/cyber.2017.0669.
View
19.
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(11):e30642.
PMC: 8694238.
DOI: 10.2196/30642.
View
20.
Smith S, Kao E, Mackin E, Shah D, Simek O, Rubin D
. Automatic detection of influential actors in disinformation networks. Proc Natl Acad Sci U S A. 2021; 118(4).
PMC: 7848582.
DOI: 10.1073/pnas.2011216118.
View