Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach

dc.contributor.author Ruiz, Jeanette
dc.contributor.author Featherstone , Jade D.
dc.contributor.author Barnett, George A.
dc.date.accessioned 2020-12-24T19:49:12Z
dc.date.available 2020-12-24T19:49:12Z
dc.date.issued 2021-01-05
dc.description.abstract Vaccine misinformation online may contribute to the increase of anti-vaccine sentiment and vaccine-hesitant behaviors. Social network data was used to identify Twitter vaccine influencers, their online twitter communities, and their geolocations to determine pro-vaccine and vaccine-hesitant online communities. We explored 139,433 tweets and identified 420 vaccine Twitter influencers—opinion leaders and assessed 13,487 of their tweets and 7,731 of their connections. Semantic network analysis was employed to determine twitter conversation themes. Results suggest that locating social media influencers is an efficient way to identify and target vaccine-hesitant communities online. We discuss the implications of using this process for public health education and disease management.
dc.format.extent 6 pages
dc.identifier.doi 10.24251/HICSS.2021.480
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/71096
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Socia Media and Healthcare Technology
dc.subject social networks
dc.subject twitter
dc.subject vaccine hesitancy
dc.title Identifying Vaccine Hesitant Communities on Twitter and their Geolocations: A Network Approach
prism.startingpage 3964
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